representative learning design in dynamic interceptive...

Representative Learning Design in

Dynamic Interceptive Actions

Ross Andrew Pinder BSc. (Hons.) Sport & Exercise Science

MSc. (Distinction) Sport & Exercise Science

A thesis submitted in fulfilment of the requirements for admission to the degree of

Doctor of Philosophy

School of Exercise & Nutrition Sciences Queensland University of Technology

Brisbane, Australia - 2012

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Keywords:

action; complex systems; cricket; dynamic interceptive action; ecological dynamics;

ecological validity; fast ball sport; interceptive actions; learning design; meta-stability;

movement organisation; perception; pursuit tracking; representative design; task

constraints; video-simulation; visual saccades

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Abstract

The overarching aim of this thesis was to investigate how processes of perception and

action emerge under changing informational constraints during performance of multi-

articular interceptive actions. Interceptive actions provide unique opportunities to study

processes of perception and action in dynamic performance environments. The movement

model used to exemplify the functionally coupled relationship between perception and

action, from an ecological dynamics perspective, was cricket batting. Ecological dynamics

conceptualises the human body as a complex system composed of many interacting sub-

systems, and perceptual and motor system degrees of freedom, which leads to the

emergence of patterns of behaviour under changing task constraints during performance.

The series of studies reported in the Chapters of this doctoral thesis contributed to

understanding of human behaviour by providing evidence of key properties of complex

systems in human movement systems including self-organisation under constraints and

meta-stability. Specifically, the studies: i) demonstrated how movement organisation

(action) and visual strategies (perception) of dynamic human behaviour are constrained by

changing ecological (especially informational) task constraints; (ii) provided evidence for

the importance of representative design in experiments on perception and action; and iii),

provided a principled theoretical framework to guide learning design in acquisition of skill in

interceptive actions like cricket batting.

Chapters 1 and 2 of the thesis provide an overview of the programme of work, and a review

of literature pertinent to the research aims, and empirical and theoretical Chapters.

In Chapter 3, movement organisation of cricket batters’ actions was analysed under

changing informational task constraints. Results showed that each distinct set of task

constraints led to significant variations in emergent patterns of movement control.

Removal of advanced information sources from a bowler’s action when batting against a

ball projection machine caused significant delays in movement initiation, resulting in

reduced peak bat swing velocities and a reduction in quality of bat-ball contact when

compared with batting against a ‘live’ bowler. When coupling their responses to a near life-

size two dimensional video simulation, batters were able to use information from the

bowler’s action to enable fidelity of initial behavioural responses consistent with the task of

batting against a ‘live’ bowler. However, without the requirement to intercept a ball or

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actual ball flight information, significant variations in downswing initiation timing and peak

bat velocities were observed. In Chapter 6 of this thesis, further evidence demonstrated

how perception and action are affected under changing informational constraints provided

by the use of ball projection machines. Batting performance and visual search strategies of

developmental level cricket batters (n = 5) were again assessed when facing a ‘live’ bowler

and a ball projection machine. Findings demonstrated that visual strategies of

developmental batters under moderate to high temporal demand (≈ 28 m·s-1) are

significantly affected by differences in pre-release information under changing task

constraints. When facing a ‘live’ bowler compared to ball projection machine tasks, batters

initiated pursuit tracking of the ball earlier after release, tracked the ball for a longer

proportion of early flight and performed fewer visual saccades. Frequency of visual

saccades was not indicative of highly skilled performance, as implied in previous research;

in fact higher ranked batters performed fewer visual saccades (≈ 60% of trials) than their

lower ranked counterparts (≈ 100%). The findings of Chapter 6 suggest that previous

interpretation and understanding of the role of visual saccades, and their relationship to

visual pursuit tracking behaviours, may have been limited by the use of artificial task

designs which do not allow coupling of action to information sources representative of a

performance context of intercepting a ball delivered from a ‘live’ opponent. The removal of

representative action requirements in experimental design is currently limiting or even

misleading understanding of perceptual-motor skill in sport. Findings from this phase of the

research provided evidence for the concern of generality of performance data from

experimental and learning tasks to those tasks representative of a performance context.

Modelling the performer as a complex system using theoretical concepts from Dynamical

Systems Theory (DST) and Ecological Psychology, and allowing performance to occur in a

representative context provided further unique insights into current understanding of

perception and action. The aim of Chapter 7 of this thesis was to examine the role of meta-

stability in an externally-paced interceptive action. Here, data on meta-stability in

performance of multi-articular hitting actions by skilled junior cricket batters (n = 5) were

reported. Results demonstrated that, at a pre-determined distance to the ball, participants

were forced into a meta-stable region of performance where rich and varied patterns of

functional movement behaviours emerged. Participants adapted the organisation of

responses, resulting in higher levels of variability in movement timing in this performance

region, without detrimental effects on the quality of interceptive performance outcomes.

This Chapter provides the first evidence for the presence of meta-stability in the

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performance of multi-articular interceptive actions involving co-adaptation with an

opponent. Flexibility and diversity of movement responses were optimised using

experiential knowledge and careful manipulation of key task constraints of the specific

context. Designing research and practice tasks which focus on candidate meta-stable

regions results in rich and varied action responses, and may allow for the development of

better perceptual and decision making behaviour, and a deeper understanding of the

information-based regulation of human performance in dynamic environments.

Collectively, the empirical findings reported in this thesis demonstrate how the

representative design of experimental task constraints in the study of human movement

behaviour is a critical concern in effectively capturing performer-environment relationships,

and functional perception and action responses. Accordingly, in Chapters 4 and 5 of the

programme, the relevance of Egon Brunswik’s (1956) concept of representative design was

highlighted for sports sciences, practice and experimental design. In this thesis, the

significance of ensuring representative design in analyses of human behaviour was

exemplified by the study of the use of ball projection technology in the acquisition of

interceptive batting actions. Links were drawn with ideas on learning design in the

constraints-led approach to motor learning and nonlinear pedagogy. The adoption of a new

term, representative learning design was proposed to help sport scientists, experimental

psychologists, and pedagogues recognise the potential application of this key idea to

ensure functionality and action fidelity in experimental and learning environments.

Representative learning design theoretically captures how sport scientists can use insights

from ecological dynamics to ensure that experimental and practice task constraints are

representative of the particular performance context to which data are expected to be

generalized toward. These theoretical and methodological concerns are exemplified in the

use of ball projection machines in experimental and learning design in perceptual-motor

behaviour. The use of ball projection machines in designing developmental and elite fast

ball sports skill acquisition programmes is not a trivial issue, since they play a crucial role in

reducing injury incidence in players and coaches. A compelling challenge for sports science

is to provide theoretical principles to guide how and when projection machines might be

used for acquisition of ball skills and preparation for competition in developmental and

elite sport performance programmes; questioning the role of ball projection machines in

the first instance has provided a significant methodological advancement to the area. On a

practical level, the findings provided coaches with an opportunity to target perceptual

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training using specific video-simulation designs, and provided cautionary evidence for the

overuse of ball projection machines in training situations.

Underpinning movement analyses in sports performance with concepts from ecological

dynamics provided unique insights into the perception-action processes of dynamic

interceptive actions. Results of this doctoral research have implications for the future

design of experimental tasks, and research is needed to assess how the manipulation of

task constraints or targeting of meta-stable regions in representative performance

simulations affect perception and action of individuals of different skill levels. Results also

have critical implications for the pedagogical practice of sports coaches. The design of

learning environments which effectively capture and enhance functional and flexible

movement responses representative of performance contexts should be constructed using

principled theoretical and methodological frameworks advocated throughout this thesis.

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Table of contents

Keywords: ________________________________________________________________ i

Abstract __________________________________________________________________ ii

Table of contents _________________________________________________________ vi

List of Figures ____________________________________________________________ ix

List of tables _____________________________________________________________ xii

List of abbreviations ______________________________________________________ xiii

Statement of original authorship _____________________________________________ xv

Acknowledgements ______________________________________________________ xvi

Research outputs _______________________________________________________ xviii

Chapter 1 – Introduction and thesis outline _____________________________________ 1

1.1. Introduction _______________________________________________________ 2

1.2. Statement of the research problem ____________________________________ 4

1.3. Significance of the studies ____________________________________________ 5

1.4. Structure of the thesis _______________________________________________ 6

Chapter 2 – Literature review ________________________________________________ 9

2.1. Dynamic interceptive actions ________________________________________ 10

2.2. Ecological dynamics ________________________________________________ 11

2.3. Constraints on complex neurobiological systems _________________________ 11

2.4. An ecological approach to perception and action _________________________ 14

2.5. Brunswikian concepts ______________________________________________ 15

2.6. Representative experimental design as a basis for the study of perception and

action in sport __________________________________________________________ 20

2.7. Methods and approaches to studying perception and action in cricket batting _ 21

2.8. Two-visual systems model ___________________________________________ 31

2.9. Adopting ecological concepts for task design in sport _____________________ 39

2.10. Summary and conclusions ___________________________________________ 43

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Chapter 3 – Representative experimental and practice task design in dynamic interceptive

actions _________________________________________________________________ 47

3.1. Abstract ________________________________________________________ 48

3.2. Introduction _____________________________________________________ 49

3.3. Method _________________________________________________________ 53

3.4. Results _________________________________________________________ 59

3.5. Discussion _______________________________________________________ 64

Chapter 4 – Representative Learning Design: A theoretical framework for research and

practice design in sport ____________________________________________________ 73

4.1. Abstract ________________________________________________________ 74

4.2. Introduction _____________________________________________________ 75

4.3. Ecological validity and representative design ___________________________ 75

4.4. Representative task design in the study of perception and action in sport ____ 78

4.5. ‘Representative learning design’ _____________________________________ 79

4.6. Summary ________________________________________________________ 83

Chapter 5 – Principles for the use of ball projection machines _____________________ 87

5.1. Abstract ________________________________________________________ 88

5.2. Introduction _____________________________________________________ 89

5.3. The problem of practice volume _____________________________________ 90

5.4. Implications for skill acquisition ______________________________________ 91

5.5. Principles for Future Work __________________________________________ 93

5.6. A future role for ball projection machines? _____________________________ 96

5.7. Conclusion ______________________________________________________ 99

Chapter 6 – Visual strategies of developmental level cricket batters under distinct practice

task constraints _________________________________________________________ 103

6.1. Abstract _______________________________________________________ 104

6.2. Introduction ____________________________________________________ 105

6.3. Method ________________________________________________________ 109

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6.4. Results _________________________________________________________ 116

6.5. Discussion ______________________________________________________ 123

6.6. Conclusion ______________________________________________________ 127

Chapter 7 – Meta-stability and emergent performance of dynamic multi-articular

interceptive actions ______________________________________________________ 131

7.1. Abstract ________________________________________________________ 132

7.2. Introduction _____________________________________________________ 133

7.3. Method ________________________________________________________ 136

7.4. Results _________________________________________________________ 140

7.5. Discussion ______________________________________________________ 144

7.6. Conclusion ______________________________________________________ 146

Chapter 8 – Epilogue ______________________________________________________ 149

8.1. Introduction _____________________________________________________ 150

8.2. Phase one _______________________________________________________ 151

8.3. Phase two _______________________________________________________ 154

8.4. Phase three _____________________________________________________ 156

8.5. Conclusion ______________________________________________________ 159

Appendix - The changing face of practice in cricket batting _______________________ 161

Bibliography ____________________________________________________________ 173

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List of Figures

Figure 1.1

Structure and overview of the programme of research.

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Figure 2.1.

Brunswik’s lens model (taken from Araújo & Kirlik, 2008).

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Figure 2.2.

Simplified model of the two visual systems in visual anticipation

(taken from van der Kamp et al., 2008).

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Figure 3.1

Experimental set-up for ‘live’ bowler, ball machine and video

simulation conditions, respectively.

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Figure 3.2

Mean group batting quality of contact (QoC) scores across

interceptive experimental task constraints (B, BM) and shot type.

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Figure 3.3

Differences in the timing and initiation of front foot movement (FFM)

and front foot placement (FFP) relative to bat-ball contact, when

facing three distinct experimental tasks.

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Figure 3.4

Differences in the timing and initiation of backswing (BS) and

downswing (DS) relative to bat-ball contact, when facing three

distinct experimental tasks.

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Figure 3.5

Mean group differences in peak backswing heights (above left) and

step lengths (above right) during an attacking and defensive shot

under three distinct experimental task constraints.

62

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Figure 3.6

Mean group horizontal bat end-point velocities for the forward drive

shot across three distinct experimental tasks.

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Figure 5.1

A principled theoretical framework for the future design of

experimental and practice tasks involving ball projection machines.

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Figure 6.1

Side and above views of experimental setup.

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Figure 6.2

A participant wearing full protective equipment and mobile eye-

tracking unit.

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Figure 6.3

Individual (a & b) and group (c) performance scores under changing

task constraints.

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Figure 6.4

Individual and group pursuit tracking responses under changing task

constraints; a) PTI; b) PTD; c) group means.

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Figure 6.5

Individual and group visual saccade responses under changing task

constraints; a) Number of saccades (as a % of total trials); b) Timing of

visual saccade (as % of release-bounce point); c) group means.

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Figure 6.6

Group means for the relationship between visual pursuit tracking and

occurrences of saccades. PTI = Pursuit track initiation; PT-end = the

offset of the pursuit track duration.

121

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Figure 6.7

Individual batter mean percentage scores across all conditions for

visual tracking variables. Batters are ordered by skill level (highest to

lowest, left to right).

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Figure 7.1.

Side and above views of experimental setup. Performance regions are

numbered with respect to distance of ball pitching from batter.

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Figure 7.2.

Pictorial representations of types and consistency of movement

responses (i.e. shot by direction and batters’ primary movement) in 4

distinct performance regions categorised by ball pitching location.

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Figure 7.3.

Unfolding movement organisation for; a) Batter 2 b) Batter 4, in 4

distinct performance regions.

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Figure 7.4.

Estimations of variability (SD) of key movement initiations during the

unfolding interceptive action for 5 skilled junior performers (batter 1-

5 from top to bottom) in 4 distinct performance regions.

143

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List of tables

Table 3.1 Peak horizontal bat end-point velocity (m·s-1), and time (s) at which

peak velocity occurred relative to bat-ball or predicted bat-ball point of

contact, for forward drive and forward defensive shots. 61

Table 6.1

Participant information. CPE= Competitive playing experience; BPW = Self-

report average of ‘balls’ per week practiced using a ball projection machine;

QoC = Quality of contact; FoBS = Forcefulness of bat swing. 102

Table 6.2

Correlations of batters skill ranking with visual tracking variables 115

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List of abbreviations

2D Two-dimensional

3D Three-dimensional

B Bowler

BM Ball machine

BMB Ball machine ‘blocked’

BMR Ball machine ‘random’

BR Ball release

BS Backswing

DS Downswing

FFM Front foot movement

FFP Front foot placement

FoBS Forcefulness of bat swing

IFM Initial foot movement

PTD Pursuit track duration

PTI Pursuit track initiation

QoC Quality of Contact

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Statement of original authorship

The work and publications contained in this thesis has not been previously submitted to

meet the requirements for an award at this or any other higher education institute. To the

best of my knowledge and belief, the thesis contains no material previously published or

written by another person except where due reference is made. In cases where Chapters

are based on published outputs, reference has been made to those outputs.

Signed: Date:

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Acknowledgements

I would like to acknowledge and thank a number of people for their great support in the

generation of this thesis and programme of work.

First, thank you to QUT and HMS (now E&NS) for the scholarship funding and opportunity

to complete a programme of work in Brisbane, Queensland. Furthermore, thanks to all the

staff and the level 3 post-grad students who have directly or indirectly shaped my

programme of work through lengthy discussions, feedback and presentation advice. In

particular, thanks to Matt Dicks, Dan Greenwood, and Elissa Philips. Special thanks to Hugo

Kerhervé for his contribution; our conversations sparked what later became the position

paper and published output – I look forward to seeing some of your more outlandish ideas

come to fruition over the next few years. Thanks also to various journal editors and

anonymous reviewers over the past couple of years who have provided rich and

constructive feedback, and to Pedro Passos and Marc Portus for their feedback at

confirmation and final seminar stages, respectively.

I would like to thank Brisbane Boys Grammar School for allowing me to complete my

research with them, and each and every participant involved for their interest, passion and

commitment to being part of this work. Special mention has to go to Darren Holder -

Thanks for your continued support and organisation during testing, and willingness to ‘find

a way’ when the weather got the best of us.

I cannot possibly thank Jonny Headrick enough for his help. Not only did he risk his life

several times in the name of research, but he never grew tired of days spent working to the

sounds of Bruce Springsteen. Thanks Boss – I owe you.

Thanks to Dave Mann for his expertise guidance, patience, and ability to maintain some

forward momentum with our various transitions between academic roles. Thanks too for

your initial sourcing of equipment and willingness to fly up to ‘sunny’ Brisbane on the

promise of organised testing. We still have a long way to go to address all of those ideas we

came up with at the Story Bridge Hotel! Thanks to Vishnu Sarpeshkar for his help during

that data collection session.

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Thanks to Duarte Araújo for his contribution to the early stages of this programme of work.

Your expertise and clarity, on theoretical aspects in particular, were invaluable and I am

greatful for your contribution on two key outputs from this programme of work. I look

forward to working with you more in the future.

My sincere thanks to Keith Davids and Ian Renshaw for their expertise, guidance, and

patience. I couldn’t have asked for a better balance in a supervisory team, nor could I have

expected such rich and quick feedback through every stage of this programme of work.

Thank you for the invitation and opportunity to come to Brisbane to work with you in the

first instance. From our first meet at Hallam 5 years ago, to giving Keith and his over 45s

team a stern talking to, to waiting to see what form of public transport Ian will arrive on

(we find it funny even if you don’t!), to sitting having a drink with my parents discussing my

inability to demonstrate the golden thread of a research programme in an abstract; its been

a privilege, and here’s to more of the same.

Thanks to Sian for being part of my life through all of this, and for helping me keep things in

perspective – “…just remember, in the grand scheme of things your research doesn’t mean

anything...” Thanks for all your support.

Finally, all my love and thanks to Mum, Dad, Scott & Leanne. At times we try and kid

ourselves that access to the internet and Skype makes it easier to be this far away from

each other, but the truth is it isn’t easy at all. That you have supported and encouraged me

unconditionally means everything. It made me so happy that you were able to be out here

while I was moving between PhD student and full time academic roles; see Dad, I promised

I’d get a real job eventually! Mum, I’m sorry I couldn’t put a border on it. I miss you all.

xviii

Research outputs

Peer-reviewed journal articles:

Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011a). Manipulating informational

constraints shapes movement reorganization in interceptive actions. Attention,

Perception & Psychophysics, 73, 1242-1254.

Pinder, R. A., Davids, K., Renshaw, I., & Araújo, D. (2011b). Representative learning design

and functionality of research and practice in sport. Journal of Sport & Exercise

Psychology, 33, 146-155.

Pinder, R. A., Renshaw, I., Davids, K., & Kerhervé, H. (2011). Principles for use of ball

projection machines in elite and developmental sport programmes. Sports Medicine,

41(10), 793-800.

Pinder, R. A., Davids, K., & Renshaw, I. (2012). Meta-stability and emergent performance of

dynamic multi-articular interceptive actions. Journal of Science and Medicine in Sport.

Davids, K., Araújo, D., Vilar, L., Renshaw, I., & Pinder, R. A. (in press). An Ecological

Dynamics approach to skill acquisition: Implications for development of talent in

sport. Talent Development & Excellence.

Pinder, R. A., Renshaw, I., & Davids, K. (under review). The Role of Representative Test

Design in Talent Development: A Comment on “Talent identification and promotion

programmes of Olympic athletes”. Journal of Sports Sciences.

Book Chapters:

Pinder, R. A. (2010). The changing face of practice for developing perception: action skill in

cricket. In I. Renshaw, K. Davids & G. J. P. Savelsbergh (Eds.), Motor Learning in

Practice: A Constraints-Led Approach (pp. 99-108). London: Routledge.

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Conference presentations (oral):


cricket. Australasian Skill Acquisition Research Group Conference – 11th-12th July

2009, Queensland University of Technology, Brisbane, Australia.

Conference presentations (poster):

Pinder, R. A., Davids, K. & Renshaw, I. (2009). The use of video simulations in cricket

batting. Evolution of the Athlete – 2nd-4th November. Brisbane, Australia.

Pinder, R. A., Davids, K., & Renshaw, I. (2011). Learning design for the use of ball projection

technologies in sport. Technologies in Sport Symposium – 20th-22nd September.

Dunedin, New Zealand.

Invited presentations:

Pinder, R. A. (2011). Unstable performers are adaptable performers. Presentation to

coaches. 23rd September. Sport Otago: Dunedin, New Zealand.

Other:

Pinder, R. A. (2010). Representative Design and Visual Anticipation in Dynamic Interceptive

Actions. PhD. Confirmation of Candidature Presentation – 19th April 2010,

Queensland University of Technology, Brisbane, Australia.

Pinder, R. A. (2011). Research portfolio and PhD implications. Presentation to academic

staff – 5th May 2011. University of the Sunshine Coast, Sippy Downs, Australia.

Mann, D. L., Abernethy, B., & Farrow, D. (2011). Vision in Batting: examining vision to

enhance skill learning in cricket batting (Scientific Report). Brisbane, Australia: Cricket

Australia. [Methods information included from Chapter 6]

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Dedicated to Mum & Dad, for everything

Chapter 1 – Introduction and thesis outline

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1.1. Introduction

A limitation in psychological science has been the neglect of the role of the environment in

experimental design, with an over-emphasis on the study of processes within the organism

(Brunswik, 1956; Dunwoody, 2006). The design of experimental task constraints that

effectively capture functional organism-environment relationships has been a prominent

concern in experimental psychology (e.g., Brunswik, 1956; Davids, 2008; Dhami, Hertwig, &

Hoffrage, 2004; Le Runigo, Benguigui, & Bardy, 2005; Rowe, Horswill, Kronvall-Parkinson,

Poulter, & McKenna, 2009), and in medical (Renshaw, Davids, Shuttleworth, & Chow, 2009)

and motor learning research (Davids, 2008). This concern was also recently expressed in a

critique of research on visual anticipation in fast ball sports (van der Kamp, Rivas, van

Doorn, & Savelsbergh, 2008), which has generally failed to maintain the functional coupling

of perception and action processes in experimental designs (Dicks, Davids, & Araújo, 2008;

van der Kamp et al., 2008). For example, previous work on perception and action has

demonstrated significant differences in measures of movement behaviour (such as visual

search or perceptual expertise) between laboratory conditions and conditions

representative of performance contexts (e.g., video versus in situ or 'naturalistic' tasks;

Dicks, Button, & Davids, 2010; Mann, Williams, Ward, & Janelle, 2007). Consequently, there

is a need to reassess traditional experimental designs used to investigate human behaviour,

and in particular visual perception, with reference to environmental constraints in specific

performance contexts. An important concept in this challenge is representative design.

Egon Brunswik (1956) outlined the concept of representative design over half a century ago,

emphasising the importance of organism-environment relations in the study of human

behaviour. Brunswikian concepts have still not been integrated into psychological research

(Le Runigo et al., 2005), with researchers traditionally opting for systematic designs for

experimental control, jeopardizing the generalizability of research findings (Araújo, Davids,

& Passos, 2007). Generalizabilty is central to the ideals of Brunswik’s (1956) notion of

representative experimental design, which proposes that experimental stimuli must be

sampled from an organism’s natural environment so as to be representative of the stimuli

to which it is adapted and to which experimental data are intended to be generalized

(Brunswik, 1956). Brunswikian ideals are harmonious with tenets of Gibson’s (Gibson, 1979)

theory of direct perception which emphasised the reciprocal relationship between

processes of perception and action in organism-environment interactions. In studies of

sport, representative design supports the generalization of task constraints in experiments


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to the task constraints encountered during performance (Araújo, Davids, & Hristovski,

2006; Davids, 2008). The integration of Brunswikian and Gibsonian ideas propose that in

order to attain representative experimental design, experimental task constraints used to

study processes of perception and action in sport need to allow participants to pick up and

use information from the environment to support functional movement responses (for an

overview see Warren, 2006).

However, a criticism of existing methodologies in the study of perceptual-motor expertise

in sport is that they have failed to implement representative experimental task designs in

research (Davids, 2008; Dicks et al., 2008; van der Kamp et al., 2008). A major concern is the

passive nature of perception in the absence of functional actions, where experimental

designs have failed to provide informational constraints to encompass relevant perception

and action processes (Davids, 2008; Dicks et al., 2008; van der Kamp et al., 2008). Research

in contemporary neuroscience has proposed that two interconnected neural streams

function within the visual cortex: a ventral (‘vision for perception’) stream which is

predominantly responsible for detection of information within the environment, and a

dorsal (‘vision for action’) stream which is responsible for visual control of action (Milner &

Goodale, 1995, 2008). By emphasising the importance of movement control in perception,

van der Kamp and colleagues (2008) applied the two-visual system model to extant visual

anticipation research, proposing a new framework for experimental designs to capture the

complementary contributions of both ventral and dorsal streams, and the functionality of

perception and action processes. These advances raised serious questions about the

validity of ubiquitous occlusion paradigms and video simulations in research on visuo-motor

performance in sport, which were criticised for failing to maintain functional couplings of

perception and action (for a comprehensive review, see van der Kamp et al., 2008). It is

important to note when considering the development of a theoretical framework that this

is not just considered a weakness in perceptual-motor research in sport science. For

example, the critical failing of talent identification tests to consider representative design

has been outlined (Vilar, Araujo, Davids, & Renshaw, in press). A major contribution of this

thesis is the creation of an overarching framework for sport scientists, to ensure that the

research and practice designs allow for the representative assessment of the competitive

environment (see Chapters 2, 4 and 5 for these theoretical advances).

Furthermore, technical expertise (e.g., movement organisation) research on interceptive

actions such as cricket batting (Weissensteiner, Abernethy, & Farrow, 2009a), has favoured

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the use of ball projection machines to enhance experimental control of projectile

trajectories. However, initial studies on the use of projection machines have revealed

significant differences in batting actions of participants when compared to movement

responses coordinated to a projectile delivered by a ‘live’ performer (Renshaw, Oldham,

Davids, & Golds, 2007; Shim, Carlton, Chow, & Chae, 2005). Consequently, current

understanding in perceptual-motor expertise in sport (in visual perception and technical

research programmes) may have been compromised by utilising experimental designs

which are not representative of typical performance environments. This concern is

mirrored in the practical use of ball projection machines for the development of

interceptive skill in fast ball sports (see section 2.7).

1.2. Statement of the research problem

Cricket batting is an ideal task vehicle for the study of perception and action in dynamic

interceptive actions. However, a criticism of existing methodologies in the study of

perceptual-motor expertise in sport is that they have failed to implement representative

experimental task designs in research (Davids, 2008; Dicks et al., 2008; van der Kamp et al.,

2008). Consequently, current understanding in perceptual-motor expertise in sport (in

visual perception and movement (technical) research programmes) may have been

compromised by utilising experimental designs that are not representative of typical

performance environments, in which individuals are permitted to assemble functional

movement behaviours based on the pick-up of prospective information (e.g., Montagne,

2005). Our understanding of perceptual-motor abilities in dynamic performance

environments may be at best limited, or at worst biased or misleading (Savelsbergh & Van

der Kamp, 2000; van der Kamp et al., 2008). Furthermore, practice task constraints using

ball projection machines are used heavily in development programmes (in addition to in

experimental designs), and there may be a need to re-address the use of specific practice

tasks in the design of learning and practice environments. Additionally, much of the

research analysing perceptual-motor skill in sport (particularly in cricket) has utilised

expertise paradigms comparing experts with novices, and there is a need to re-examine

these issues while targeting important performance developmental stages. The trend to

focus on expertise effects means there is currently limited understanding of the acquisition

of perceptual-motor skills at important developmental stages. This is a critical concern

when considering the high prominence of ball projection machines during these


5

developmental stages, and the non-linear nature of learning between novice and expert

performance.

Therefore, the current programme of work addresses the following questions:

(i) How does changing the experimental task and informational constraints affect

the movement organisation (Chapter 3 & Chapter 7) and visual strategies

(Chapter 6) of cricket batters actions?

(ii) Do pre-release kinematic information sources facilitate the ongoing regulation

of dynamic interceptive actions or provide a representative task for enhancing

affordance perception (Chapter 3)?

(iii) What are the implications of ‘representative experimental design’ for

experimental, learning and practice design in sport science (Chapter 4), and

more specifically fast ball sport (Chapter 5)?

1.3. Significance of the studies

This programme of research concerns a conceptual, theoretical and methodological

rationale for enhancing knowledge about the acquisition of perceptual-motor behaviour in

dynamic interceptive actions. The programme examines the influence of different

ecological task constraints on representative task design by assessing athletes’ movement

organisation and visual strategies of interceptive actions, in addition to examining how

performers functionally adapt in dynamic situations under changing task constraints. The

programme of work provides theoretical and experimental implications for development of

perceptual-motor ability in sports science research. Furthermore, the research provides a

principled framework for researchers, coaches and pedagogues for the use of ball

projection technology in sport.

The overarching aim of this programme of work was to re-assess current experimental and

practice task designs used in perceptual-motor research in dynamic interceptive actions.

The programme of work promotes the concept of representative design through sport

science and nonlinear pedagogy, and provides a theoretical framework for the future

design of experimental and learning designs in sport. Theoretically, the PhD programme

contributes to the integration of Brunswikian concepts by providing empirical evidence to

demonstrate the importance of representative experimental design (see Chapter 3), and

6

provides a principled theoretical rationale for future experimental research (see Chapter 4).

This thesis also adopts this developed framework and provides a principled approach for

the use of ball projection technology in fast ball sports such as cricket batting (see Chapter

5). Furthermore, considering the movement model of a cricket batter as a complex system

allows for the advancement of theoretical concepts in complex systems literature. Here, it

is exposed how multi-articular actions in sport can provide insights into meta-stability and

demonstrate how complex systems contextually adapt under changing task constraints (see

Chapter 7). Methodologically, the programme provides a broad critique of previous

experimental designs, and provides empirical evidence to demonstrate the importance of

representative design for future studies in perceptual-motor expertise in sport.

Furthermore, the programme enabled us to begin to understand the precise differences in

informational constraints provided by a variety of experimental task designs used

throughout sport science and motor-learning, and address some of the key concerns that

have been highlighted in previous methodologies (e.g., video simulations, ball projection

machines). Practically, the examination of batters actions under changing task constraints

will provide implications for the use of different practice and learning designs in fast ball

sport; for example, limitations of ball projection machines, or the possibilities of enhancing

affordance perception using video simulations. Additionally, the assessment of visual and

movement behaviour demonstrates current benefits and limitations of existing tasks (e.g.,

ball projection machines), and begins to provide insights into how they may be used to

provide more representative practice designs.

At the time of lodgement, this thesis has yielded four published peer-review journal articles

(with 1 currently under review), a book chapter, and multiple conference and applied (e.g.,

coaching) presentations.

1.4. Structure of the thesis

The current programme of work is submitted as a traditional thesis, and includes a

combination of initial background literature, Chapters based on published journal articles or

work being finalised for submission for peer-review. There is, therefore, a proportion of

repetition throughout the thesis. This is necessary to allow the Chapters to be read as

standalone articles, and neatly demonstrate the contribution given to the literature at each

stage of the PhD programme. In such instances edits have been made to ensure language

and formatting consistency throughout the thesis, and additional information is included


7

where necessary. The PhD programme was the result of an emergent process, where the

development of ideas and theoretical positions was based on previous Chapters. As a

result, independent Chapters link neatly back to back demonstrating this progression (see

Figure 1.1).

Figure 1.1. Structure and overview of the current programme of research

Phase 1 - Development and demonstration of the research problem: movement organisation under changing task constraints in sport

•Chapter 2 – Literature review: Review of literature and identification of a problem

•Chapter 3 – Empirical examination of previous experimental and practice task designs in cricket batting.

Phase 2 - Creation of a theoretical framework: Representative Learning Design

•Chapter 4 – Development of a global framework for experimental design in sport science research

•Chapter 5 – Development of a specific framework for the use of ball projection machines in elite and developmental sports programmes

Phase 3 - Examination of visuo-motor behaviour under changing task constraints

•Chapter 6 – Visual strategies under changing practice task constraints in cricket batting

•Chapter 7 – Exploratory empirical examination of the emergence of meta-stability in dynamic interceptive actions in fast ball sport.

Phase 4 - Review

•Chapter 8 – Epilogue: Review of the theoretical, methodological and practical implications

Chapter 2 – Literature review

9


The following review of literature firstly describes how the use of dynamic interceptive

actions (such as movement skills in cricket) allows for a rich environment for the study of

processes of perception and action (Stretch, Bartlett, & Davids, 2000). Secondly, it

introduces concepts from Ecological Dynamics which contextualise and underpin the

programme of research. The analysis of literature demonstrates how these concepts can be

specifically applied to the study of perceptual-motor behaviour in sport, and discusses the

possible consequences for motor learning research, sports science, fast ball sport, and

nonlinear pedagogy.

10

2.1. Dynamic interceptive actions

Interceptive actions are prevalent in everyday life, with humans required to complete tasks

as routine as grasping objects or tools, shaking hands or placing a foot on a kerb when

crossing the street (Davids, Savelsbergh, Bennett, & van der Kamp, 2003). Critical to these

actions is the ability to successfully detect relevant information from the environment to

guide decisions and actions. Dynamic interceptive actions provide scientists with

opportunities to study processes of cognition, perception and action in real-world contexts.

These processes become more apparent and constrained in interceptive actions in fast ball

sports (Ranganathan & Carlton, 2007), where performers have to organise movement

responses based on rapidly changing, or emerging information from the environment,

under increasing temporal demand.

Movement models from sport provide quintessential examples of dynamic interceptive

actions, and are ideal task vehicles to advance current understandings of perception and

action. Importantly, they exemplify the functional coupling of perception and action, the

synergetic relationship between performer and environment, and demonstrate the

importance of representative experimental task design (Davids, Renshaw, & Glazier, 2005;

Dicks et al., 2008). For example, it is estimated that skilled cricket batters, who can face

bowling speeds of up to 160 km·h-1, need to differentiate trajectories in depth of ball to a

0.5° precision. Additionally, Regan (1997) demonstrated that response timing precision

have margins of failure at these extremes of ± 2.5 ms at movement execution. Interceptive

abilities such as these under severe temporal and spatial demands demonstrate the key

role of perceptual processes (referred to in the literature as perceptual expertise), with

temporal demands of fast ball sports going beyond the intrinsic limitations in visuo-motor

delays and movement times (van der Kamp et al., 2008). Researchers have, therefore,

concluded that information available before the onset of unambiguous ball flight is

essential to success in fast ball sports (Abernethy & Zawi, 2007; Jackson & Morgan, 2007;

Shim, Carlton, & Kwon, 2006). Consequently, over the past quarter of a century there has

been a significant increase in research focussing on perceptual skill in sport, particularly in

assessing visual anticipation, defined as the accurate prediction of future events based on

partial or incomplete sources of information (Poulton, 1957). Severe time constraints on

action provide an opportunity to analyse the mechanisms involved in the regulation of

movement responses to successfully satisfy specific task constraints (Davids et al., 2005;


11

Montagne, 2005; Montagne, Cornus, Glize, Quaine, & Laurent, 2000; Renshaw & Davids,

2006; Tresilian, Oliver, & Carroll, 2003).

2.2. Ecological dynamics

Ecological dynamics encompasses Ecological Psychology and Dynamical Systems Theory

(DST). DST is a functionalist framework for understanding neurobiological movement

coordination, and views the individual as a complex biological system composed of many

independent but interacting subsystems (Araújo et al., 2006; Clarke & Crossland, 1985).

Complex systems approaches have been used to study rich patterns of coordination in

weather systems, human brains, animal collectives and movement of collections of

individuals in team sports (e.g., Araújo, Davids, Bennett, Button, & Chapman, 2004; Bak &

Chialvo, 2001; Kauffmann, 1993). Ecological dynamics conceptualises the human body as a

complex system composed of many interacting parts and motor system degrees of

freedom, leading to emergent patterns of behaviour under changing constraints during skill

acquisition. A primary focus concerns how many interacting components (degrees of

freedom) are coordinated and controlled during interceptive or goal directed movements

(Bernstein, 1967). An ecological dynamics approach, when aligned with key models in sport

performance, provides powerful analyses of the interactions between perception and

action in ‘natural’ environments (Caljouw, van der Kamp, & Savelsbergh, 2004; Davids et al.,

2005). Ecological psychology underpinning this study proposes how information from the

environment is constantly available for pick up by performers (e.g. Gibson, 1979, 1986;

Michaels & Carello, 1981), with skilled performances characterised by exploitation of

advanced information to support the regulation of actions, such as movements of other

performers (e.g. Renshaw & Fairweather, 2000; Shim et al., 2005) or moving objects (see

Regan, 1997; Williams, Davids, & Williams, 1999).

2.3. Constraints on complex neurobiological systems

In complex neurobiological systems, states of order and rich patterns of behaviour and

coordination emerge under specific constraints, varying between different performance

contexts. A ‘constraints-based’ framework emphasises the study of movement behaviour

emerging under the continuous and cyclical interactions between the neurobiological

movement systems and the environment in which it is based (Davids, Button, & Bennett,

12

2008; Newell, 1986). In the study of perceptual expertise in sport, it is necessary to identify

the key constraints that guide action, such as in fast ball sports where movement patterns

are shaped by interacting constraints on the system. For human movement, constraints on

the individual are numerous, and limit the number of movement and outcome possibilities

available to the system (Davids et al., 2008). Constraints are defined as boundaries that

constrain the interactions of system components, and are classified into organismic

(individual), task and environmental constraints (Newell, 1986). Organismic constraints

refer to the individual’s specific characteristics, such as physical or mental aspects (e.g.,

height, level of maturation, perceptual skill). Environmental constraints are global physical

features of nature, such as ambient light, gravity or temperature (Davids et al., 2008). Task

constraints are usually more specific to performance contexts, such as task goals, specific

rules, performance boundaries, size of objects, and use of implements or tools (e.g.,

different methods of projecting a ball towards a performer in fast ball sports). As such, the

ability to vary motor performance under different performance contexts is considered a

critical feature of skill acquisition and expertise (Davids et al., 2008). Key to these

performance contexts are the availability of informational variables.

These theoretical interpretations delineate movement systems as dynamical systems due

to the numerous degrees of freedom to be coordinated and controlled during

environmental interactions. The process of self-organisation in neurobiology refers to the

adaptability of systems to the changing constraints of the environment (Davids et al., 2008).

Notably, functional patterns of behaviour of complex systems are context specific and

dependent on the interacting constraints exploited by the system. Behaviour emerges as a

variable and adaptive process dependent on the constraints on action, with research

demonstrating that task goals can be achieved through variable patterns of coordination.

Edelman and Gally (2001, p. 13763) refer to this system capability as degeneracy; the

“ability of elements that are structurally different to perform the same function or yield the

same output.” Degenerate perceptual and action sub-systems provides a complex

neurobiological system with the capacity to contextually adapt action in dynamic

interceptive actions and environments, allowing an individual to constantly regulate actions

under changing task constraints (Davids et al., 2008; Edelman & Gally, 2001). The

interaction of system components with constraints of specific experimental designs

provides a popular theoretical framework for sports scientists to use to enhance

understanding of emergent behaviour of complex systems (Araújo et al., 2006; Araújo,


13

Davids, & Serpa, 2005; Chow, Davids, Button, & Koh, 2006; Davids et al., 2005; Liu, Mayer-

Kress, & Newell, 2006).

Meta-stable or ‘dynamically stable’ states allow neurobiological systems to remain in a

state of relative coordination with the performance environment, poised between multiple

co-existing states of movement organisation, ideal for performance in dynamic sports

(Kelso, 1995, 2008). Meta-stability can be observed when a movement system performs

under a constant constellation of task constraints (e.g. distance to a target to intercept)

with a specific amount of time available during which different movement solutions are

explored. If, under specific practice task constraints, the movement system switches

between more than one movement solution (stable attractor), meta-stability is present. If,

under changing task constraints, the movement system remains in an initial attractor and

does not transit between solutions, monostability is present. Meta-stability can be

exploited during sport performance when the movement system suddenly equilibrates to a

second movement solution to satisfy changing task goals (Jeka & Kelso, 1995). Therefore,

meta-stability is an important movement system property, explaining how rich, varied and

creative movement patterns can spontaneously emerge as performers adapt their actions

to achieve particular performance goals (Guerin & Kunkle, 2004). A significant body of

behavioural neuroscience research suggests that meta-stability is central to the way human

brains work (e.g., Tognoli & Kelso, 2009), and is a common feature of effective functioning

complex systems (Kelso, 2008). Some previous work has demonstrated meta-stable

functioning in visual perception (Gross, 1996), rhythmic bimanual coordination (Jeka &

Kelso, 1995), and coordination dynamics in the brain (Tognoli & Kelso, 2009). However,

there have been few attempts to verify meta-stability in movement performance in

dynamic sport environments (Davids & Araújo, 2010).

The study of self-organisation of movement control and coordination under interacting

constraints emphasises the importance of informational sources and changing task

constraints. The interaction between organismic, environmental and task constraints

results in patterns of movement behaviour that become optimised through learning and

practice (Davids et al., 2008; Jacobs & Michaels, 2007). Critically, the adoption of a

constraints-led perspective, aligned with concepts from ecological psychology

demonstrates the important implications for learning and practice tasks in sport (see

section 2.9).

14

2.4. An ecological approach to perception and action

In order to successfully coordinate and organise interceptive actions with respect to the

environment, performers need to: i) ensure that they contact the object at the appropriate

moment in time, ii) contact with optimum velocity and force, and iii) ensure that they

contact the object with the required spatial orientation (Savelsbergh & Bootsma, 1994). To

accomplish this, performers need to be able to pick up and use precise and accurate

information to support their resulting actions. Ecological psychology is therefore

particularly concerned with the problem of how perceptual information guides action in

dynamic environments. Informational constraints (such as light arrays reflecting off objects

within the environment) help to shape ongoing behaviour and movement responses

specific to the sampled environment (Davids et al., 2008; Kugler & Turvey, 1987). The

ecological approach suggests that information is specific to objects in the environment,

which can be used directly to guide movement.

Ecological psychologists seek to understand how perceptual information guides actions in

performance environments. James Gibson’s (1979) theory of direct perception proposed

how movement is shaped and regulated using information constantly available for direct

pick up in the surrounding environment, and generated a productive body of research on

perception and action (e.g., Kugler & Turvey, 1987; Savelsbergh, Whiting, & Bootsma, 1991;

Turvey, 1990). Highly structured energy arrays from the environment can act as

informational constraints for the organisation of ongoing movement behaviour. Gibson

(1979) argued that movement creates changes in energy flow (variant or invariant), which

provides further information due to lawful relationships between movement kinetics and

environmental energy flows. This relationship leads to the proposed cyclical nature of

perception and action (Gibson, 1979; Michaels & Carello, 1981). Gibson (1979) proposed

that invariant (persistent features) and variant information can act as affordances for

action, through which the neurobiological system perceives the environment in relation to

what it offers or demands in action responses (e.g., if a cricket delivery requires the batter

to move forward or backward). Over time, performers become attuned to information

through experience and practice in different performance environments, creating

relationships between movement patterning and specific sources of perceptual information

(i.e., information-movement coupling; see also Gibson, 1979; Michaels & Carello, 1981;

Savelsbergh & Van der Kamp, 2000). This is a critical aspect of this thesis and the current


15

programmes of work, since traditional experimental designs have not always allowed for

action to occur in a performer’s typical environment (see Chapter 3; also see Chapter 5 for

an overview of this concern specifically in fast ball sport).

2.5. Brunswikian concepts

Due to the inter-dependence of processes of perception and movement, and the way in

which these neurobiological sub-systems have evolved, questions exist over the separation

of these processes in practice and experimental task design (Michaels & Carello, 1981; van

der Kamp et al., 2008). Practice or experimental designs that do not couple the processes of

perception and action will not permit perceptual and action sub-systems to function as

evolutionary designed or learned through practice (Davids, Button, Araújo, Renshaw, &

Hristovski, 2006). Historically, experimental research designs have tended to be

reductionist in nature, allowing for high levels of control and manipulation of individual

variables; this is particularly true for sports science and motor learning research (Dhami et

al., 2004). Typically, designs are concerned with ensuring that the participant sample is

representative of the population to which experimental results are to be generalized, often

referred to as external validity (Bryman, 1988) or more specifically, population validity

(Bracht & Glass, 1968). Egon Brunswik (1956, p. 39) proposed that ‘proper sampling of

situations and problems may in the end be more important than proper sampling of

subjects.’ The distinction between experimental control and field (recently referred to as in

situ: see section 2.7) research has been recognised as a false dichotomy, where the

reductionist approaches are being replaced by functionalist theoretical paradigms of

movement coordination in complex systems, under influence from ecological psychology

(Brunswik, 1956; Gibson, 1979).

Ecological psychologists have attempted to mediate the links between Gibsonian and

Brunswikian theoretical and methodological approaches (Araújo et al., 2007; Gibson, 1979;

Kirlik, 2009; Vicente, 2003), to allow for the broadening of ecological research and

development of cumulative knowledge. Current neo-Gibsonian research into event

perception coincides with the organism-environment relationships demonstrated in the

lens model (see Figure 2.1; Brunswik, 1952; Brunswik, 1956), where research is now

confronting the problem of uncertainty highlighted by Brunswik’s theory of probabilistic

functionalism (Kirlik, 2009). This perspective proposed that performer-environment

interactions are based on the pick-up of multiple sources of imperfect information from the

16

environment (for comprehensive reviews, see Hammond & Stewart, 2001b; Kirlik, 2009).

The integration of Egon Brunswik’s and James Gibson’s theoretical work could provide a

broader, more advantageous methodological approach for ecological psychology, while

maintaining the underlying beliefs of the organism-environment relationships (Kirlik, 2009;

Reed, 1996; Vicente, 2003). Brunswik’s (1956) concept of representative task design

provides a critical framework for the study of perception and action in sport (Dicks et al.,

2008). However, much of the research focussed on perceptual expertise has failed to

integrate Brunswik’s concepts, and there is a need for more applied research to exemplify

the importance of these ideals. Critically, the concept of representative design has been

entangled with another of Brunswik’s terms, namely ecological validity (Araújo et al., 2007).

This misinterpretation is a barrier in conveying these ideals throughout psychological

science, and may in part be due to the introduction of the terminology in cognitive

psychology (Neisser, 1967). This programme of research supports the integration of

Brunswikian ideals into sport science research; it firstly aims to provide empirical evidence

to demonstrate the implications of representative design for learning design in sport

research and practice (Chapter 3) before using the methodological concept of

representative design to provide a theoretical framework for future work (see Chapter 4).

Therefore, there is a need to firstly address the original concepts outlined by Brunswik

(1956).

Figure 2.1. Brunswik’s lens model (taken from Araújo & Kirlik, 2008).


17

Probabilistic functionalism and ecological validity

Brunswik’s (1956) ecological approach to cognition, perception and action was developed

through a theoretical framework referred to as probabilistic functionalism. This perspective

proposes that organism-environment interactions are based on the pick-up of multiple

sources of imperfect information from the environment (or Kirlik, 2009; for comprehensive

reviews, see Rowe et al., 2009). Put simply, individuals use a series of imperfect cues to

infer events or aspects of some unobservable state of the environment (e.g., the ways in

which performers in sport use kinematic information of another performer’s movements to

predict future intentions). As achievement of an action cannot be defined without

reference to the environment, functional systems of the individual (such as ventral and

dorsal systems: see section 2.8) are viewed as contributing factors to task goal achievement

(Kirlik, 2001). In describing organism-environment interactions, Brunswik (1956) referred to

distal variables (remote properties of the environment, such as an opponent’s intentions)

and proximal variables, or cues (information sources directly available, such as vision of an

opponent’s movements). Importantly, this process is inherently probabilistic, with variables

available from the environment providing different levels of functionality. Arguing against

the fully deterministic view, Anderson and Runeson (2008, p. 28) observed that ‘the

fundamental methodological complication is that there is a component of noise in the pick-

up of any variable, in addition to a potential nonspecificity relative to the target property.’

It could be argued that, although based on optic arrays as espoused by Gibson (1979), the

pick-up of visual informational variables from particular environments (e.g., movements of

other players or objects) can rarely, if ever, be truly specifying (leading to the pick-up of

invariants). Indeed, Kirlik (2009) surmises that an invariant can be thought of as a

perceptual cue with unit ecological validity (Vicente, 2003), and neo-Gibsonian researchers

are now demonstrating an understanding of both Gibson’s invariants, and Brunswik’s

‘nonspecifying’, or fallible cues.

Cues must be combined in a context-specific manner to provide robust organism-

environment couplings; an ability that is referred to as vicarious functioning. The ability to

identify and selectively use informational variables (or in Brunswikian terms, cues) could be

argued as one of the major factors influencing the ability to predict future behaviour of

other performers in competitive sport (van der Kamp et al., 2008). As informational sources

differ in their degrees of functionality, they may also vary in the degree to which they are

inter-correlated with each other. Skill acquisition research has all too frequently tried to

18

focus on the precise (presumed singular) source of information that perceivers putatively

use for a specific perceptual task (Withagen & van Wermeskerken, 2009), and assumed that

some form of optimal information will be available to the perceiver (Reed, 1996). Studies

focussing on perceptual learning have now begun to cast doubt over this assumption, with

individuals using different informational variables, and changing their use of variables over

time (Jacobs, Runeson, & Michaels, 2001; Runeson & Andersson, 2007; Withagen &

Michaels, 2005b). This point neatly captures the concept of system degeneracy, where

performers are able to contextually adapt under changing task constraints. The perceiver

will possibly utilise a variety of relatively reliable perceptual cues to provide themselves

with the required information to support action (Kirlik, 2009; Runeson & Andersson, 2007).

Crucially, it is these concepts that highlight the need to ensure that key informational

variables are available in particular experimental and learning environments, with further

empirical work required to exemplify this issue (see Chapter 3).

The lens model (Figure 2.1) depicts the structure of the environment and its relation to the

organism’s adjustment to that environment, essentially a pictorial representation of

vicarious functioning (Goldstein, 2006). Brunswik suggested that distal variables (e.g., a

cricket bowler’s intention to bowl a specific delivery) needed to be judged from a series of

imperfect perceptual cues (such as kinematics of the bowler’s body and arm position

before ball release). Ecological validity was originally defined as the statistical correlation

between proximal cues available in the environment (perceptual variables) and the extent

to which they depict the distal criterion state of the environment (Brunswik, 1956). The

weighting of proximal cues is referred to as cue utilization, which is aligned with

Savelsbergh and van der Kamp’s (2000) hypothesis of perceptual degrees of freedom,

where learning, and the establishment of robust organism-environment relationships (i.e.,

information-movement couplings) is analogous to Bernstein’s (1967) mastering degrees of

freedom problem. Essentially, several different couplings may be available, with learning

characterised by the refinement of established information-movement couplings. In this

regard, the utilisation of cues in particular behavioural contexts relates neatly back to

Brunswik’s (1956) concept of vicarious functioning. In essence, the lens model provides an

answer for how performers cope with complex and dynamically changing environments

through perceptual and motor system degeneracy (Davids, 2008).

Importantly, it is the nature of the information sources used to support action that is of

interest (Davids et al., 2003). By emphasising how animals use information, Gibson was able


19

to demonstrate the importance of the duality of an organism and their environment

(Turvey & Shaw, 1999). Araújo and Davids (2009, p. 6) proposed how ecological psychology

must ‘describe and measure the environment of an individual before posing questions on

how an individual may achieve knowledge about that environment’. Indeed Fajen and

colleagues (2009, p. 83) also suggested that the first stage in understanding interceptive

action is to ‘identify and provide a formal description of the information that specifies

action-relevant properties of the environment’. Ecological psychologists following the

concepts of direct perception look to analyse information-movement relationships to

understand the perceptual control of dynamic action (Fajen et al., 2009); concepts which

are exemplified by performance of interceptive actions in sport.

In recent times, researchers have generally used the term ecological validity to refer to the

external validity of research designs, and in doing so were actually referring to Brunswik’s

representative design (Araújo et al., 2007). In sports science, ecological validity has been

mistakenly presented as the study of performance, learning and behaviour under ‘natural’

task constraints (e.g., often by contrasting simple, contrived laboratory tasks such as a

pointing or manual aiming task, with ‘natural’ tasks such as catching a ball or coordinating

other multi-articular actions in sport). This is a concern for sports science as a whole, as

highlighted by the mis-use of the term in studies of the physiology of cycling performance

(Jobson, Nevill, George, Jeukendrup, & Passfield, 2008; Jobson et al., 2007).

Representative experimental design

Brunswik’s (1956) ideals have implications for all areas of research on human performance

and behaviour. Generalizabilty is central to the ideals of Brunswik’s (1956) notion of

representative experimental design (see also Hammond & Stewart, 2001b), which proposes

that experimental stimuli must be sampled from an organism’s performance environment

so as to be representative of the stimuli to which it is adapted and to which experimental

data are intended to be generalized (Brunswik, 1956). Just as participants of an experiment

must be representative of those to which the study wishes to generalize, the experimental

task constraints must also represent the environmental performance constraints to which

they are to be generalized. Generalization of findings outside defined experimental

conditions can be problematic in studying the adaptability of neurobiological systems in

dynamic environments, and emphasises the need to adequately sample environmental

constraints to provide experimental designs that analyse functional human behaviours.

20

Importantly, and as espoused through this thesis, it is important that performance

requirements are not prescribed, but rather emerge spontaneously under changing task

constraints (see Chapter 7 for an empirical example).

From a Brunswikian perspective, perceptual judgements are based on the inferences of

proximal cues (perceptual variables), with different sets of cues available in different

environmental conditions. The definition of representative design emphasises the need to

ensure task constraints of experiments represent the task constraints of the performance

environment which forms the specific focus of study. In representative design there is a

strong emphasis on the relations between the participant and the environment, which is

often neglected in traditional approaches to psychology such as cognitive psychology (e.g.,

Dunwoody, 2006). Brunswikian concepts still have not been integrated into psychological

research (Le Runigo et al., 2005), with researchers traditionally opting for systematic

designs for experimental control, jeopardizing the generalizability of research findings

(Araújo et al., 2007). In essence, there is a need for correspondence between experimental

conditions for the study of precise aspects of movement control and behaviour, and the

environmental constraints of performance. Any deviation from an experimental design

representative of the functional behaviours (e.g., links between perception and action) of

participants jeopardizes the efficacy of findings from empirical research. This is currently a

major concern for perceptual-motor research in sport.

2.6. Representative experimental design as a basis for the study of perception

and action in sport

A key concept of experimental design, particularly in perceptual skill research is the

importance of manipulating task constraints (Araújo et al., 2004), which are central to the

process of self-organisation of human movement. As Davids and colleagues (2005)

advocate, movement models of dynamic action in sport are perfectly suited to provide

representative designs of tasks for studying perception and action. In sport, representative

design supports the generalization of task constraints in learning designs to the constraints

encountered during performance (Araújo et al., 2006; Davids, 2008). Representative task

constraints therefore, implies that a performer is able to search the environment for

reliable information to support action (Dicks et al., 2008; Gibson, 1979). For example,

research into perceptual expertise has demonstrated significant differences in behaviour


21

between simplified experimental conditions and the participants’ performance setting

(Müller & Abernethy, 2006; Müller et al., 2009; Starkes, Edwards, Dissanayake, & Dunn,

1995; Williams, Ward, Knowles, & Smeeton, 2002). To exemplify, an understanding within

the anticipation in sport literature is that experimental task constraints which are not

representative of a performance context limit the advantage of experts over less skilled

performers (Abernethy, Thomas, & Thomas, 1993). Importantly, this has been largely

attributed to the removal of key information sources in experimental designs that are

present in performance contexts. In studies of visual anticipation, representative design

would be attained when the experimental task constraints replicate the constraints of the

performance environment that empiricists are attempting to analyse (Davids, 2008).

As previously discussed, the ability for performers to use information from the environment

is vital for the accurate and efficient relationship between perceptual and motor processes

in the control of action (Le Runigo et al., 2005). A key issue in ecological psychology has

recently been brought to the fore by van der Kamp and colleagues (2008), demonstrating

that many previous methodologies in visual anticipation research have failed to maintain

functional coupling between perception and action. A major concern relates to the passive

nature of perception in the absence of action, where experimental designs have failed to

provide informational and instructional constraints to encompass relevant perception and

action processes (Davids, 2008; Dicks et al., 2008; van der Kamp et al., 2008). First, there is

a need to review current methodological approaches to both perceptual and technical skill

in perceptual-motor performance, exemplified by research findings in cricket batting.

2.7. Methods and approaches to studying perception and action in cricket

batting

Previous research in cricket batting performance between skilled and less skilled

performers has been mainly focussed on visual anticipation, reaction times and perceptual

decision making (Adams & Gibson, 1989; McLeod, 1987; Penrose & Roach, 1995), visual

tracking and brain functioning (Croft, Button, & Dicks, 2010; Land & McLeod, 2000; Taliep

et al., 2008), and kinematic and kinetic factors (Stretch, Buys, Du Toit, & Viljoen, 1998;

Taliep, Galal, & Vaughan, 2007; Weissensteiner et al., 2009a). Research in cricket batting

has demonstrated a relationship between skill level and visual anticipation, consistent with

those seen in other sports (for a review, see Farrow, Abernethy, & Jackson, 2005). Until

22

recently, findings from expertise research had suggested that only skilled batters have an

ability to utilise information from the pre-release actions of a bowler (Weissensteiner,

Abernethy, Farrow, & Müller, 2008). It was understood that they gain a temporal

advantage, under severe time constraints of ball velocities typically ranging between 19 and

40 m·s-1 (Bartlett, 2003), by picking up information from limb and body orientations of the

bowler during the run-up, bound, and moment of release (Davids et al., 2005). Skilled

performers use this information to predict ‘line and length’ of deliveries from both fast

(Abernethy & Russell, 1984; McRobert & Tayler, 2005; Penrose & Roach, 1995) and left and

right handed bowlers (McRobert & Tayler, 2005), and delivery type from slow bowlers

(Renshaw & Fairweather, 2000), in addition to specifying the point of ball release (Gibson &

Adams, 1989). In contrast, previous work had suggested less skilled batters appear to gain

little information from pre-release sources, relying primarily on ball flight characteristics

(Müller & Abernethy, 2006; Müller, Abernethy, & Farrow, 2006; Müller et al., 2009;

Renshaw & Fairweather, 2000). However, research in fast ball sports is emerging to refute

these claims (Pinder, Renshaw, & Davids, 2009; Shim et al., 2005). A criticism of existing

methodologies in the study of perceptual-motor expertise in sport is that they have failed

to implement representative experimental task designs in research (Davids, 2008; Dicks et

al., 2008; van der Kamp et al., 2008). Consequently, current understanding in perceptual-

motor expertise in sport (in visual perception and technical research programmes) may

have been compromised by utilising experimental designs which are not representative of

typical performance environments, in which individuals are permitted to assemble

functional movement behaviours based on the pick-up of either or both advanced and

prospective information (e.g. Montagne, 2005). Furthermore, research has tended to

provide the same information (i.e., video simulation of a single skilled bowler) to both

skilled and less skilled batters. A concern regarding single bowler designs (e.g., possible

idiosyncrasies that may be biasing results) is also worth raising, as this is prominent in

current practices of examining batting expertise (Adams & Gibson, 1989; Renshaw et al.,

2007; Stretch et al., 1998; Taliep et al., 2007; Taliep et al., 2008; Weissensteiner et al.,

2008). Providing one single skilled bowler to a number of groups differing in skill level has a

distinct potential to bias experimental findings (e.g., skilled performers are more familiar

with the speed or action of other skilled bowlers). Additionally, much of the research

analysing perceptual and movement skill in sport (particularly in cricket) has compared

experts with novices, and there is a need to re-examine these issues while targeting

important performance developmental stages.


23

Occlusion techniques

Emerging through the leading theoretical approach of the time (information-processing),

the occlusion technique became prominent in the 1980s (Abernethy & Russell, 1987; Jones

& Miles, 1978; Salmela & Fiorito, 1979). Typically, participants from differing skill levels

view video clips of an opponent’s action (e.g., tennis serve, cricket delivery) with part of the

action selectively occluded leaving the viewer with partial sources of information, to which

they are required to respond with verbal (see Farrow & Abernethy, 2003; Weissensteiner,

Abernethy, & Farrow, 2009b), button pressing or joystick manipulations (Savelsbergh, van

der Kamp, Williams, & Ward, 2005; Taliep et al., 2008) or simplified micro-movements

(Farrow & Abernethy, 2003; Shim et al., 2005). The rationale behind this approach was to

determine the minimal information needed to make accurate predictions of future events

(Panchuk & Vickers, 2009), in line with the early research and studies of ball catching

(Whiting, 1968). This idea fitted neatly with a predictive control strategy where movements

are pre-programmed (for an overview, see: Davids et al., 2003; Dessing, Peper, Bullock, &

Beek, 2005), as opposed to an ecological approach of continuous adaptations in a

prospective control strategy (Beek, Dessing, Peper, & Bullock, 2003; Montagne, 2005).

Studies using temporal and spatial occlusion paradigms have consistently demonstrated

that ‘expertise’ in sport is characterised by the ability to process early visual cues to identify

the future intentions of an opponent. Specifically, the progressive temporal occlusion

technique has consistently demonstrated that experts are able to anticipate more

effectively than novices, and are capable of picking up useful informational variables earlier

in their opponent’s movement pattern (for a review see: Farrow et al., 2005).

To exemplify the prominence of these designs, recent work in perceptual-motor expertise

in cricket batting has used written responses and video-based occlusion for measuring

anticipation skill. For example, Weissensteiner et al. (2008) attempted to examine

anticipatory skills using a cross-section of skill levels of the developmental pathway (e.g.,

skilled and lesser skilled at U15, U20 and adult level) with reference to batter’s practice

histories. Presentation of one swing bowler’s action was via a plasma screen, with the

requirement of participants to ‘react’ to clips, randomly occluded at four time points: at the

bowler’s back foot contact, the bowler’s front foot contact, at ball release, or no occlusion.

Participants recorded one of three responses using a pen and paper within a 5s interval: if

they judged the delivery to be a full inswinger, and full outswinger, or a short delivery. It

was proposed that skilled adults and U20 batters were able to use pre-release kinematic

24

information from the bowler’s action to anticipate ball type that was not evident in other

less skilled or younger groups. However, prediction accuracies only exceeded above chance

levels under the no occlusion condition, and hours of cricket specific practice only explained

a modest percentage (13.3% and 11.4% for ball type and ball length, respectively) of the

variance in anticipatory skill. Furthermore, Taliep and colleagues (2008) have also assessed

reaction time, response selection and brain activation while skilled and less skilled batters

provided button pressing responses to video simulation of inswing and outswing bowling.

Understanding of the expert’s superior anticipatory abilities in instances such as this may

be at best limited, or at worst biased or misleading (Savelsbergh & van der Kamp, 2009; van

der Kamp et al., 2008).

In response to the concerns raised in reference to video-based occlusion methodologies,

there have been a growing number of ‘field’ studies for visual anticipation (Abernethy, Gill,

Parks, & Packer, 2001; Müller & Abernethy, 2006; Müller et al., 2009; Singer et al., 1998;

Starkes et al., 1995). It has been proposed that the use of ‘natural’ in situ experimental

conditions has been a major advance within motor learning and sports science literature

(Müller & Abernethy, 2006; Müller et al., 2009; Starkes et al., 1995; Williams et al., 2002).

This claim has been based on evidence in the visual anticipation literature demonstrating

that in situ experimental tasks allow expertise effects to be more clearly exhibited than

when using laboratory-based, video simulation methods (Müller & Abernethy, 2006; Müller

et al., 2009; Williams et al., 2002). The limitations of these latter studies are attributed to

the removal of key sources of information in experimental design and a failure to ensure

knowledge of neural system functioning underpins research designs (Davids, 2008; van der

Kamp et al., 2008). Typically, researchers have not used theoretical understanding of why in

situ task constraints facilitate the emergence of expertise effects. Nor have they ensured

that experimental task constraints support the use of functional information-movement

couplings (enabling participants to construct valid actions based on information more

representative of the performance environment). Furthermore, a prominent characteristic

of in situ task designs appears to be that experimental task constraints have been

considered with detection of information in mind, and not perception and action.

For example, Müller et al. (2009) used liquid crystal occlusion goggles (with vision removed

at various periods before bat-ball contact) to demonstrate the use of both early and late

ball flight information to guide bat-ball contacts (with ball speeds of 110-120 km·h-1).

Previously, Müller and Abernethy (2006) suggested that when facing slow bowlers, there


25

was little evidence to demonstrate that gross body movements (such as front foot

movement) were based on advanced information. Furthermore, low-skilled batters were

unable to use early ball flight to guide lower body positioning, whereas experts were able

to use both early and late ball flight information. Critically, the authors provided no

information regarding ball speeds generated by bowlers, with low-skilled batters facing

highly skilled spin bowlers. It could be argued that for lower skilled batters, the ability to

make accurate bat-ball contacts in this situation is not a reflection of perceptual ability, but

a combination of perceptual (e.g., anticipatory) and movement (technical) skill.

In situ research designs have been driven by technological advances (such as the use of

liquid crystal occlusion goggles), and the focus of demonstrating superior expertise effects,

generally by comparing experts with absolute novices (e.g., Müller et al., 2009). As a result,

in situ task designs have enabled researchers to allude to the importance of the coupling of

perception and action (due to superior expertise effects), without the underpinning

relationship to a theoretical rationale. This weakness is only exacerbated by the progression

of research based on findings from experimental designs that do not attain representative

design, and were established through an information-processing perspective. Furthermore,

the continual use of the underlying occlusion technique, even in performance settings (e.g.,

with ‘live’ bowlers) is questionable based on recent insight from contemporary

neuroscience (e.g., Milner & Goodale, 1995, 2008), and concepts of perceptual and

perceptual-motor system degeneracy through ecological dynamics (e.g., use of different

combinations of visual information).

The validity of findings from occlusion studies has been questioned on the grounds that

they have failed to preserve the functional coupling between perception and action (Farrow

& Abernethy, 2003; Farrow et al., 2005; van der Kamp et al., 2008), by using simple

response modes unreflective of task constraints in performance contexts. Importantly, this

is a key factor in the modelling of two visual systems for perceptual-motor behaviour,

which is discussed below (see section 2.8). Research needs to develop a more principled

theoretical rationale for this line of work to provide a comprehensive framework to guide

future experimentation on perceptual-motor expertise in sport performance. The

contribution of this thesis to this literature can be found in Chapter 4 (also see Chapter 5

for the development of this framework into a principled model for the use of ball projection

technology in sport performance).

26

Visual search

Previously, there have been assumptions that athletes are required to fixate and pursuit

track an object for skilled interception (Regan, 1997), or that high levels of visual function

are required for skilled performances to be sustained. Indeed, many people believed that

Sir Donald Bradman, widely regarded as the greatest cricket batsmen in the history of the

sport, benefitted due to superior visual function and reaction times. However it is reported

that Bradman was discharged from the army due to poor eyesight (Glazier, Davids,

Renshaw, & Button, 2005; Hutchins, 2002) and recent studies by Mann and colleagues

(2010; 2007) demonstrated that no discernible reductions in batting performances were

evident under increasing levels of myopic blur that resulted in impairment of foveal vision

under moderate and high temporal demands (moderate ball speed in cricket batting: 30-40

m·s-1). It has been surmised, therefore, that skilled performance in sport is not necessarily

dependent on the pickup of accurate trajectory information of an object to successfully

intercept it (Mann et al., 2010). Recently, it has been proposed that performers are unable

to pursuit track for the entire duration of a target’s approach; for example in cricket

batting, it has been demonstrated that performers used a combination of target pursuit

tracking and visual saccades when intercepting balls delivered from a ball projection

machine. Visual saccades appear to enable a visual ‘catch-up’ of foveal vision in instances

where the visual system is unable to “keep up” with the ball flight (Land & McLeod, 2000).

However, to successfully intercept high speed balls it is also generally accepted that

performers require the ability to perceive ball trajectory information (e.g., angle of

approaching ball, predicted bounce point) quickly and accurately in order to support shot

and movement response selection. Indeed, information about ball flight elicited from a

bowlers’ action has been shown to contribute towards batters judgement of ball delivery

type (Müller & Abernethy, 2006; Müller et al., 2009).

Smooth visual pursuit tracking strategies during human performance allows for the

extraction of detailed and meaningful information from the environmental context.

Tracking objects within foveal vision over longer periods of total flight time increases the

perceptual acuity of the object (e.g., the speed and angle of an approaching ball to be

intercepted). However, Spering and Gegenfurtner (2008) recently concluded that eye

movement strategies, such as the ability to smoothly track objects, is highly context

dependent, with changes to visual strategies affected by numerous factors, such as

absolute or angular speed of an approaching object, or the predictability of that objects


27

flight (McPherson & Vickers, 2004). Land and McLeod (2000) published their seminal and

highly cited paper more than ten years ago; assessing the visual strategies of three cricket

batters under ball projection machine task constraints. Land and McLeod (2000) assessed

the eye movements of three cricket batters (skilled, experienced and novice) when facing a

ball projection machine under moderate temporal constraints (25 m·s-1). Findings

demonstrated that batters picked up trajectory information for a period of 100-150 ms

after the release of the ball from the machine (equating to 50-80% of total ball flight),

before making an anticipatory saccade to the predicted bounce point. Findings suggested

that batters cannot ‘pursuit track’ the ball for the duration of ball-flight, therefore requiring

them to pick up trajectory information as soon as possible to predict bounce point and/or

delivery type. Croft, Button and Dicks (2010) recently attempted to reassess the findings of

Land and McLeod to establish if there was a critical velocity at which predictive saccades

were required; however, they found that no simple relationship existed between projection

speed and the initial tracking duration. Croft et al., (2010) found that under slow to

moderate temporal constraints (17-25 m·s-1), experienced sub-elite batters used a variety

of highly individual strategies, with considerable variation beyond a group tracking mean of

between 63 and 71% of ball flight. Large within and between-participant variability

demonstrated that batters used vastly different strategies both before, and immediately

after ball release (e.g., saccade or track); a finding consistent in other fast ball sports

(McPherson & Vickers, 2004; Singer, Cauraugh, Chen, Steinberg, & Frehlich, 1996). Some

batters tracked the ball immediately following ball release and then for the majority of ball

flight; a finding consistent with skilled batters in Land and McLeod’s (2000) study. It may be

that ball deliveries with longer flight times due to bouncing closer to the batter, and/or

moving at slower velocities, allow for increases in tracking duration and do not exceed the

limitations of the visual tracking processes. These findings suggest the ability of a batter to

pick up ball flight as early as possible may afford a longer tracking duration. Previous

interpretations suggest that the occurrence of a visual saccade may be due to a critical

change in vertical velocity (e.g., short balls that bounce further from the batter and are

delivered on a steeper angle from release) (Land & McLeod, 2000). Latencies between the

release and initial tracking of the ball in both instances may account for the appearance of

predictive saccades, with some skilled batters in Croft et al.’s study able to track directly

from release and therefore may in fact be able to counter this need to ‘catch up’ with the

ball.

28

The use of ball projection machines in studies of perception and action

Recent work has also proposed that performance of skilled batters is distinguishable from

that of less skilled batters in various technical abilities including significantly earlier

initiation and completion of front foot movements, coupling of the front foot movement to

bat swing, bat swing tempo (ratio of back swing to downswing), and increased consistencies

in timing of the downswing, when facing a ball projection machine (with a velocity of 120

km·h-1/ 33 m·s-1) (Weissensteiner et al., 2009a).

However, Renshaw et al. (2007) examined the movement coordination and timing of four

skilled batsmen during the forward defensive stroke, against a ‘live’ bowler and ball

projection machine at the same speed (26.76 m·s-1). Significant adaptations were observed

under the two different task constraints. The backswing in the ball projection machine

condition varied greatly, but was coupled to ball release (0.02 ± 0.10 s after ball release),

whereas against the bowler, initiation of the backswing occurred later (0.12 ± 0.04 s). It has

now been shown that less skilled, developing batters are comparably affected by the

changing tasks constraints of a ball projection machine (Pinder et al., 2009; also see Chapter

3). Data showed that there were significant adaptations to movement timing and

coordination for both a defensive and attacking stroke, with initiation of the backswings

occurring after ball release (drive: 0.06 s; defence: 0.06 s) against the ‘live’ bowler, but

significantly later against the ball projection machine (drive: 0.15 s; defence: 0.14 s). In

contrast to this result, Renshaw et al. (2007) reported that when skilled batsmen faced a

bowling machine, the point of backswing initiation varied greatly but occurred around the

point of ball release. Less skilled, developing batters are comparably as affected by the

changing task constraints in practice. With the removal of advanced information when

batters practiced against a ball projection machine (e.g., no pre-delivery bowler

information), batters demonstrated a prospective control strategy based on the emergence

of unambiguous ball flight information; evidenced by delayed movement initiations when

compared to a ‘live’ bowler condition (Pinder et al., 2009). These findings are supported by

similar work in tennis, with significant delays in movement initiation when responding to a

‘cloaked’ ball projection machine compared with a ‘live’ hitter (Shim et al., 2005). Changes

in spatio-temporal movement responses suggest that different information sources are

used to support prospective control of action, meaning that there may be a need to re-

address previously unquestioned work (e.g., Land & McLeod, 2000). Further work is

required to understand how performance, visual search and movement organisation are


29

affected under distinct task constraints of ball projection machines, when compared to a

representative task of facing a ‘live’ bowler. This is a particular concern given the

widespread acceptance of the findings of the Land and McLeod (2000) study (based on 3

performers of widely varying skill level). Additionally, the issue is important on a practical

level given the tendency for developmental programmes in cricket to utilise projection

machines to provide large volumes of blocked practice while using ball projection machines

(e.g., via practice where a performer is aware in advance of the predictable, consistent

bounce point of the ball).

Differences between contexts may be that batting against a ball machine removes the

critical information sources present in a performance context representative of facing an

opponent (e.g., removal of bowler’s movement information such as angle of arm at

release). Failure to be able to attune to this crucial information source leads to a critical

delay in movement initiations because early ball flight needs to be sampled before the

bounce point can be identified and the batter can make a decision to move forward or

backward to intercept the ball. It is this increased temporal demand that ultimately results

in a reduction in batting performance. Based on this body of work, it is intuitive to suggest

that differences should exist in visual strategies under changing task constraints in cricket

batting. However, until now few attempts have been made to assess visual strategies in

cricket batting, and none that have compared visual search strategies when batting under

ball projection machine constraints compared to a performance context of facing a ‘live’

opponent.

Changing the informational constraints on action might result in less representative

practice designs, and changes to a performer’s acquisition of functional movement control.

This idea has been exemplified in cricket batting research. Stretch and colleagues (1998)

demonstrated that batters adapted spatio-temporal characteristics of emergent action

when facing a ‘live’ opponent, depending on the required shot response to different

bowling trajectories through the pickup of advanced kinematic information and from early

ball flight. These adaptations to action ensured that batters contacted the ball at the right

time with the correct spatial orientation (Savelsbergh & Bootsma, 1994). As a result, when

facing a ‘live’ bowler, experienced batters executed attacking drives which reached peak

horizontal velocity 0.02 s before bat-ball contact (Stretch et al., 1998); consistent with

findings in other fast ball sports (e.g., baseball, McIntyre & Pfautsch, 1982; softball, Messier

& Owen, 1984; golf, Shibayama & Ebashi, 1983). Despite these findings, very little work has

30

focused on how differing spatio-temporal responses under varying task constraints affect

batting performance outcomes or bat velocity (force control), beyond simple performance

measures (e.g., see Mann et al., 2010). Clearly, further work is needed to compare

perceptual-motor organisation when batting against a ‘live’ performer and against ball

projection machines to observe how advance kinematic information from a bowler’s

actions shapes behaviour.

McLeod (1987) proposed that the major limiting factor between skilled and less skilled

batters was the ability to organise and coordinate motor system degrees of freedom.

However, there is little research into movement organisation expertise, predominantly

because of a difficulty in accurately testing these outcomes. For example, Stuelken and

colleagues (2005) analysed video footage of a batter’s actions from first class and

international matches. However, the absence of joint markers brings into question the

findings of this study as movement variability cannot be reliably determined from no-

marker conditions (Araújo, 2007).

In one other exception, Taliep and colleagues (2007) compared kinematic variables of

performance by skilled and less-skilled cricket batters when completing micro-movements

such as ‘shadow’ front foot drives (an attacking shot) performed against ‘realistic projected

video footage’ in a screened simulation of the performance environment. However, since

no comparative studies of movement behaviour under video simulation conditions and a

representative task of batting against a ‘live’ opponent currently exist, it is not known

whether life-size video simulations provide a representative task for batters. This lack of

clarity is mainly due to: (i) the removal of the performance of an interceptive action in

many simulation designs (e.g., decoupling of perception and action); and (ii), to previous

research showing differences in information pick up from 2D video displays compared to

competitive performance environments (see Dicks, Button, et al., 2010). Furthermore,

without knowledge of the effects of manipulation of ball length in previous studies (varying

perceptual information and ball trajectories), it is unknown whether batters can attune to

small but critical changes in delivery characteristics (e.g., between two different ball landing

positions), when that information is presented in video simulations. Critical information

sources may be removed completely (e.g., removal of a bowler’s movements when using

ball projection machines), but they may also be present but much harder to detect in a 2D

display than in the competitive performance environment.


31

2.8. Two-visual systems model

Research in contemporary neuroscience proposes that two separate but interconnected

neural streams are discernible in the cerebral cortex during visual perception (Milner &

Goodale, 1995, 2008). The dorsal stream picks up visual information for the control of

movements (referred to as vision for action processes), such as the spatio-temporal

characteristics of arm movements (kinematics), so that interceptive actions are completed

at the right place at the right time (see section 2.4). The ventral stream is primarily involved

in the pick-up of visual information to gain knowledge about the environment (i.e., vision

for perception processes), such as the recognition of objects based on size or colour, or

information for tactical decisions on what action is appropriate in given situations. Critically,

the ventral stream has only indirect connections to the pre-motor cortex, such as

projections to the ventral pre-frontal cortex proposed to be involved in memory and

decision-making processes (Rossetti & Pisella, 2002). Vision for action and for perception

processes can be differentiated on the spatial and temporal scales on which they are based.

The ventral stream is involved in the recognition of properties of objects such size, shape,

colour or relative speed, which are assumed to be reliant on world-centred or allocentric

information. However, human movement control requires more precise (metric)

information about the location, speed and orientation of an object (e.g., when intercepting

a ball) relative to the current movement of the performer. Therefore, the primary goal of

the dorsal system is the detection of body-centred, egocentric informational sources. The

concern over separating the two visual systems is based on the contribution of the ventral

system for action. Information detected by the ventral system is used to decide on what the

current situation affords, whereas under specific circumstances this system can in fact

dominate movement control (therefore allocentric information). Empirical research has

demonstrated these contributions in visual illusions (see also, van der Kamp & Masters,

2008 for examination with soccer goalkeepers; van Doorn, van der Kamp, & Savelsbergh,

2007), pantomimed actions (Goodale, Jakobson, & Keillor, 1994), and actions accompanied

by verbalisation (Rossetti, 1998; Rossetti & Pisella, 2002). It has been noted that

verbalisation is particularly prevalent in novice performers, and therefore it is speculated

that novices may rely heavily on the ventral system until the dorsal system, in time,

‘becomes more automated’ (Milner & Goodale, 1995; van der Kamp, Oudjeans, &

Savelsbergh, 2003; van der Kamp et al., 2008). This claim has yet to be empirically verified;

however, the importance of such claims further highlights the current concerns of previous

methodological paradigms in perceptual-motor behaviour.

32

The key point of Milner and Goodale’s (1995) model is that rather than one singular

perceptual process, visual anticipation and resulting online movement control involve the

functional integration of two separate visual systems (van der Kamp et al., 2008). The

perception of affordances from the environment is supported by the ventral stream, while

the dorsal stream simultaneously uses informational sources from the environment to

guide movement responses. The importance of this interaction has recently been alluded to

in understanding interceptive actions in fast ball sports (van der Kamp et al., 2008). Next,

the framework proposed by van der Kamp and colleagues (2008) is discussed, along with its

proposed implications for perceptual-motor research in sport, and how this could be

supported by ecological psychology.

Two-visual systems in perceptual-motor control

Emphasising the importance of movement for perception, van der Kamp et al. (2008)

examined the value of Milner and Goodale ‘s (1995) two visual system organisation in the

cortex, for experimental designs in visual anticipation research. Figure 2.2 highlights the key

principles behind the model, demonstrating the interaction between the two systems

during one sequence of a tennis receiver’s return action. The key point of the model is the

initiation point of the receiver’s action relative to the end point (e.g., release or racquet

contact) of the opponent’s action. It is proposed that, although both streams show parallel

engagement, the point of movement initiation is the crucial discrimination point with

regards to relative contributions (e.g., the dominance of the dorsal stream). It is argued that

the dorsal system may even provide a large contribution for the initial kinematic

parameterization of the possible action afforded, therefore increasing the dorsal

contribution immediately before movement onset (e.g., Goodale & Milner, 2004). The

ventral system obtains information from the environment to set the constraints on action

(e.g., from opponent’s movement kinematics, opponent’s court location, and possibly early

ball flight), while it is the dorsal stream that predominantly controls the movement

response. In the case depicted, movement onset occurs before ball release; therefore

movement would initially be based on opponent’s movement kinematics. Research is

beginning to show that movement onset after the point of release (e.g., under less time

constrained conditions) may be just as reliant on opponent’s movement kinematics

(Abernethy et al., 2001; Abernethy & Zawi, 2007; Shim et al., 2005; Ward, Williams, &

Bennett, 2002). For example, Shim et al. (2005) demonstrated how the removal of


33

advanced sources of information of a hitters action significantly limited the distance they

were able to cover on court (i.e., they were able to move earlier against a ‘live’ hitter

compared with a ball projection machine, despite movement commencing after racquet-

ball contact or ball release from the machine). However, simplified micro-movements limit

the validity of these studies, with affordances for action (e.g., recognising cross-court or

down-the-line intentions of opponent’s) not necessarily requiring metrically precise

information.

Figure 2.2 illustrates that van der Kamp and colleagues (2008) do not propose that the two

visual systems work as sequential processes, nor does pre-flight information relate solely to

the ventral system, or ball-flight information to the dorsal system. Applied to cricket

batting, their ideas suggest that the batter may utilise the ventral system to perceive the

intended ‘length’ (distance of ball bounces from the batter) of the delivery, but make use of

the dorsal system to prospectively control action and make the final decision on shot type

after movement initiation (see previous section 2.7; also see Stretch et al., 1998). Actors

have to not only perceptually judge affordances for action, but must physically move to

intercept the ball; in this respect, the use of visual information in fast ball sport involves

action as well as perception (Savelsbergh & van der Kamp, 2009).

34

Figure 2.2. Simplified model of the two visual systems in visual anticipation (taken from van der

Kamp et al., 2008). Model represents the observable temporal events seen in fast ball sports (top),

informational sources available to the performer (middle), and the proposed contributions of the

ventral (affordance perception) and dorsal (movement control) systems (bottom). Note: the deeper

the colour, the larger contribution of the visual system.

Implications for sports science research

Van der Kamp et al. (2008) proposed that, while previous experimental designs may have

provided some limited insights into perceptual expertise, behavioural tasks which lack

representative design (which the authors confuse with ecological validity – see section 2.5)

may not have allowed the dorsal pathway for perception and action to function as evolved.

Their critical analysis questioned current understanding of perceptual expertise in dynamic

interceptive actions (van der Kamp et al., 2008), focusing specifically on weaknesses of

occlusion and video-based simulation methodologies which have been consistently used in

sports research (e.g., Rowe et al., 2009; Sebanz & Shiffrar, 2009). Typically, these

methodologies have required participants to react to presentation of visual stimuli with

verbal (see Farrow & Abernethy, 2003), button pressing or joystick manipulations

(Savelsbergh et al., 2005; Taliep et al., 2008) or simplified micro-movements (Farrow &

Abernethy, 2003; Shim et al., 2005). Here, the concern over separating the visual systems

opponent’s action

release point

movementinitiation

interception point

ball flight

Temporal events in fast ball sports

receiver’s action

affordance perception

movement controlInvolvement of two visual systems

action kinematicsAvailable information toreceiver opponent’s court position

anticipation

opponent’s action

release point

movementinitiation

interception point

ball flight


receiver’s action




opponent’s action

release point

movementinitiation

interception point

ball flight


receiver’s action




anticipation


35

may be exacerbated due to the dominance of the ventral system upon verbalization.

Importantly, the reactions produced by participants in these experiments bear little relation

to the complex, information-movement coupled responses coordinated in performance

contexts (e.g., batting 'responses' used by Taliep et al., 2008). Furthermore, not all studies

using occlusion techniques have reported unambiguous findings related to expertise

(Abernethy, 1988; Houlston & Lowes, 1993). Some have demonstrated a diminished

expertise effect when ball flight information was presented to participants (Abernethy,

1988; Isaacs & Finch, 1983; Williams & Burwitz, 1993). For example, data from a number of

key occlusion studies have demonstrated considerable spatial errors in predicting the

landing location of an object even under full vision conditions (e.g., including ball flight) for

both novices and experts (Abernethy et al., 2001; Abernethy & Russell, 1987; Houlston &

Lowes, 1993; McMorris & Colenso, 1996). These findings support the notion that occlusion

studies tend to require participants to only utilise the metrically less precise ventral system,

which may be detrimental for expert performance due to their reliance on the dorsal

system contribution.

These perceived weaknesses have led some researchers to assess movement responses to

simulated actions presented on a screen, typically without occlusion of pre-release or early

ball flight information (Rowe & McKenna, 2001; Shim et al., 2005; Williams, Ward,

Smeeton, & Allen, 2004). This is an important issue since the point of occlusion typically

occurring at the point of ball release by an actor in a simulation can vary substantially (e.g.,

discernible differences in arm angle between short and full deliveries in cricket). However,

the use of simple micro-movements (e.g., taking one step on pressure pads) and specific

instructions for participants to react ‘as quickly as possible’ may have confounded

conclusions from these experiments (for a comprehensive critique, see van der Kamp et al.,

2008, p. 121). Requirements to react to simulated images and the regulation of movement

control by information (i.e., information-movement coupling) are not alike, because only

the latter emphasizes functioning of an integrated dorsal cortical pathway. Functional

actions are achieved with the contribution of both cortical pathways in performance (e.g.,

judging the catchableness of fly balls: Oudejans, Michaels, Bakker, & Dolné, 1996), and the

traditional designs of visual anticipation research has only tended to engage participants’

ventral system by limiting their involvement to identifying information for action. As such,

the occlusion methodologies may not truly reveal how vision guides skilled interceptive

actions, or how information from opponent’s (biological) body movement available before

release can facilitate movement execution (van der Kamp et al., 2008).

36

There is little known about the extent to which affordance perception (opportunities for

action the environment offers, see Gibson, 1979) relies on movement kinematics and early

ball-flight, as studies have failed to fully integrate the dorsal system in experimental

designs. For more representative experimental designs in the visual anticipation literature,

technical (large screen displays and near life-size video simulations) and methodological

advances (use of multi-articular movement models that couple perception and action) need

to be integrated in to the research. Some researchers have begun to address these issues;

however questions still exist over the movement responses required of participants. For

example, Shim et al. (2005) analysed the effect of expertise and display mode on

anticipation performance using a micro-movement in response to an occluded tennis

action. It was observed that novices’ anticipation accuracy decreased when they

transferred from a two-dimensional video simulation to a ‘live’ performer condition.

Experts, on the other hand, coupled movement responses more accurately to information

from the actions of a ‘live’ performer when compared to two-dimensional video simulation

and point light displays. Furthermore, Ranganathan and Carlton (2007) demonstrated that

baseball batters were more accurate in predicting delivery type when they were not

required to move in response (i.e., give verbal responses), but were better at using the first

100 ms of ball-flight information when movement responses were required. These findings

demonstrate that there is currently some contention in the literature about the

effectiveness of two-dimensional video simulations. Researchers have described the

possibilities of using video simulations to enhance perceptual skill in novice performers

(Abernethy et al., 2001; Jackson & Farrow, 2005; Rowe & McKenna, 2001; Williams, Ward,

& Chapman, 2003; Williams et al., 2004). However, from a two-visual system perspective, it

is not known whether this type of training could result in more efficient action production,

without the full integration of the dorsal system. It is expected that video simulations may

indeed enhance affordance perception, with research designs placing predominant focus

on the ventral system. The critical point is that it is proposed that both systems must be

trained together and not in isolation (van der Kamp et al., 2008). Research is required to

clarify the issues raised regarding video-based simulations and coupling of perception and

action processes in experimental designs. Simulated environments have been shown to

enhance skill acquisition of perception and action processes (Araújo et al., 2005), and

Brunswikian theoretical approaches (i.e., probabilistic functionalism) suggest that task

simplification and simulation may be used in training with the appropriate theoretical


37

rationale. This theoretical rationale and contribution to the literature can be found in

Chapters 4 and 5.

Van der Kamp and colleagues (2008) also proposed that one of the fundamental failings of

current visual anticipation research, highlighted by data on the two-visual system, is that it

is still not clear if pre-ball release information (e.g., kinematic information from an

opponent’s action and body orientation) facilitates the regulation of action in participants.

Shim et al. (2005) demonstrated that there was a latency of around 50 ms before the onset

of action for a tennis return against a ‘cloaked’ bowling machine in comparison to a ‘live’

hitter (movement initiated 180 ms after ball release from machine compared with 130 ms

after the racquet-ball contact point of a ‘live’ hitter). It was concluded that expert tennis

players were able to use movement pattern information from an opponent to determine

shot requirement (backhand or forehand), significantly reducing response delay times, and

enabling better anticipation to increase their court coverage. Given that the fastest

latencies in the dorsal system are considered to be in the region of 100 ms (e.g., Caljouw et

al., 2004), the validity of these conclusions is unclear; however, there is some evidence for

significant differences in movement timing and coordination when batting in cricket against

a projection machine and against a ‘live’ bowler (Renshaw et al., 2007). It has been shown

that the use of ball projection machines (with velocities ranging between 26-30 m·s-1) lead

to significant differences in timing and coordination of both skilled and less skilled batters

responses when compared to facing a ‘live’ bowler projecting a ball at the same speed

(Pinder et al., 2009; Renshaw et al., 2007). This is a critical concern for perceptual-motor

research, especially technical studies of movement organisation, which have tended to

favour the utilisation of ball projection machines in experimental designs (Croft et al., 2010;

Land & McLeod, 2000; Weissensteiner et al., 2009a).

Previous work on the two-visual system model has relied on tasks involving fewer degrees

of freedom, such as reaching and grasping an object. These studies have demonstrated

significant differences in gaze patterns and gaze shifts, as opposed to simply perceiving and

estimating object lengths (van Doorn, van der Kamp, de Wit, & Savelsbergh, 2009). Van

Doorn and colleagues (2009) demonstrated that the functional distinction between the two

visual streams encompasses both the processing and detection of information. Notably, the

functional demands of perception and action (both singularly, and coupled) place different

constraints on an individual’s detection of information. In terms of dynamic interceptive

actions, the use of tasks which are not representative of specific performance contexts, or

38

removal of the perception-action link for perceptual training and research, could entail

disparate information pick-up and use. Clearly, further work is needed to compare

movement performance and visual search behaviour against a ‘live’ performer and against

ball projection machines to observe the use of advance kinematic information to anticipate

and organise action. Critically, there is a need to firstly understand the precise differences

in informational constraints between a ‘live’ bowler and ball projection machines, before

researching how these practice tasks may be used in learning designs that attain

representative design. Specifically in experimental design, there may be a need to rule out

any potential confounds which may be present when simply comparing machine and ‘live’

bowler tasks, such as priming from machine specific sources (see Renshaw et al., 2007), in

addition to assessing alternative experimental designs (e.g., large screen simulations – see

section 2.7).

Ecological psychology and the two-visual systems model

Identifying the role of the two-visual system for perceptual-motor performance provides a

critical advance of research in perception and action. However, it has been highlighted that

there are current issues in the conceptualisation of expertise between van der Kamp et al.’s

(2008) proposals, and the theoretical insights of ecological psychology (Araújo & Kirlik,

2008). An ecological view, based on organism-environment relationships, suggests that it is

the individual who perceives and acts upon information from the environment holistically,

and not simply one or more of his/her functional systems (Withagen & Michaels, 2005a).

Van der Kamp and colleagues ascribed psychological attributes to the brain or systems of

which it is composed, leading to the view of expertise in visual anticipation characterised by

‘better’ functioning and integration of the two visual systems. However, an ecological

viewpoint characterises expertise as the ability of individuals to actively engage in

dynamical interactions within functional environments; in essence, expertise would be

captured as the ability to successfully adapt performance under varying constraints of the

environment (Araújo, 2007; Kirlik, 2006). Using concepts from ecological psychology to

underpin the two-visual systems model, may allow for a more comprehensive framework

for the basis of future study of visual anticipation in sport. Importantly, the adoption of

neo-Gibsonian and Brunswikian ideals will ensure that organism-environment mutuality

and reciprocity be upheld in experimental design. For example, van der Kamp et al. (2008)

recognised the importance of Gibson’s insights in explaining visual guidance of action;

although there is currently little theoretical support for assessment of action-based


39

judgements in perception and action in sport. It is proposed that the adoption of

Brunswikian concepts in this instance could provide valuable insights and theoretical

support for the progression of our current understandings of judgement for action (Araújo

& Kirlik, 2008; Kirlik, 2001, 2009). Furthermore, van der Kamp et al. (2008) questioned the

efficacy (ecological validity) of occlusion methodologies and video simulation tasks that

typically required participants to respond with verbal, written, button pressing or micro-

movement responses. Araújo and Kirlik (2008) clarified that van der Kamp and colleagues

were alluding to the representative design of these methodologies, according to Brunswik’s

(1956) original insights. This programme of work promotes the integration of neo-

Gibsonian and Brunswikian schools of thought in providing the theory for underpinning

future experimental design (Kirlik, 2001, 2009). The use of practice and learning tasks in

cricket batting are used to exemplify how the concepts of representative experimental

design have striking implications for all kinds of learning designs in sport (see Chapters 3, 4,

5 and 6)

2.9. Adopting ecological concepts for task design in sport

From the viewpoint of ecological psychology, learners attempt to converge on useful

perceptual variables to support action in specific performance environments; this is called

the education of attention, or perceptual attunement (Fajen et al., 2009; Gibson, 1966;

Jacobs & Michaels, 2002). The role of practice involves becoming attuned to the different

informational variables available in different performance contexts (Davids et al., 2008) and

calibrating movement responses and coordination patterns (information-movement

couplings) to those variables. Since the perceptual information will be unique and

constrained by each individual setting, it is important that the informational variables

available in the performance setting are sampled in a practice environment; allowing

learners to develop their capacity for detecting more reliable informational cues for

supporting action. Jacobs and Michaels (2002) proposed that the two distinct phases of

constructing information-movement couplings are: (a) the education of attention to key

informational sources, and (b) the fine tuning of movements to a ‘‘critical information

source” (Davids et al., 2005), or “sources.” The development of expertise in sports

performance requires the establishment of a link between information and movement,

which is refined and attuned in the long term (Araújo, 2007); performers require the

calibration between information and movement (coupling) in order to refine action-

relevant information (Montagne, 2005). Intuitively, the removal of any of the critical

40

sources (informational variables) during developmental stages could have major

consequences for skill acquisition; impeding perceptual learning and resulting in

unintended changes to the control and coordination of action. While practice task

constraints may contain some informational variables that are available to support

learners’ actions during practice tasks (i.e., cues used while batting against a ball projection

machine), it is imperative that learners are provided with opportunities to attend to and

calibrate movement responses to informational variables representative of performance

contexts. Practice task constraints that provide informational variables for pick up by

learners that are available during performance can be considered to be high in

representative task design (see Araújo et al., 2007). Changing the informational constraints

in practice environments may lead to the design of less representative practice tasks by

altering availability of informational variables, resulting in changes to a learner’s acquisition

of functional movement patterns (Beek, Jacobs, Daffertshofer, & Huys, 2003).

Ecological concepts for nonlinear pedagogy

Recent work in physical education and coaching science has demonstrated how principles

of ecological dynamics can underpin practice in a nonlinear pedagogy (Chow, Davids,

Button, Shuttleworth, et al., 2006; Chow et al., 2007; Hammond & Stewart, 2001a, 2001b).

The basis of nonlinear pedagogy emphasises the manipulation of key task constraints

during learning to allow functional movement behaviours to emerge in specific sports and

physical activities. In the pedagogical practice of coaches, sports scientists and physical

educators, experimental design equates to the design of practice and training

environments. The constraints of training and practice need to adequately replicate the

performance environment so that they allow learners to detect affordances for action and

couple actions to key information sources within those specific settings. In the area of

sports science and performance analysis there is a need for greater awareness of: a) the

concept of Brunswik’s (1956) representative experimental design; and b), the requirement

for these methodological ideals to be adopted in all kinds of practice, training and learning

programme design (e.g., Renshaw et al., 2009).

Empirically, to examine the degree of association between behaviour in an experimental

task with that of the performance setting to which it is intended to generalize, there has

been a recognition of the importance of Stoffregen et al.’s (2003) concept of action fidelity

(Araújo et al., 2007). In the use of flight simulations, Stoffregen et al. (2003, p. 120)


41

described action fidelity as the ‘fidelity of performance’, and proposed that fidelity exists

when there is a transfer of performance from the simulator to the simulated system. In this

respect, practice, training and learning tasks could be viewed as simulations of the

performance environment which need to be high in fidelity. The validity of action fidelity

can be measured by analysing task performance in detail. For example, measures of task

performance in sport, such as time taken to complete a task and observed movement

organisation during performance would provide satisfactory measures to assess action

fidelity of simulated training, practice and learning environments (Araújo et al., 2007). In

support, van der Kamp et al. (2008) advocated that measures of movement organisation be

assessed during visual anticipation in experimentation. This programme of research

investigates characteristics of movement timing, control and organisation, and affordance

perception as demonstrated in sport psychology (Araújo et al., 2006; Araújo & Kirlik, 2008).

Representative design requires the comparison of the fidelity of practice/training task

constraints with those constraints experienced in performance environments. Sport

pedagogy therefore requires closer alignment with current motor learning theory (see

Renshaw et al., 2009), with the importance of representative design and action fidelity in

sport training and development programmes being a major research focus for this

programme of research. These ideas are expressed in the following section through the

example of learning design in cricket batting.

Practice and learning design in cricket batting

Based on theoretical ideas previously outlined, an important question in this programme of

research is: How does changing the practice task constraints (availability of informational

variables) affect the control and organisation of dynamic interceptive actions such cricket

batting? The use of ball projection machines is a highly common practice, particularly in

cricket. The clear advantage of these machines is that they alleviate the workload required

of bowlers; with overuse injuries being a major concern, particularly in adolescence

(Dennis, Finch, & Farhart, 2005). Additionally, ball projection machines can provide

relatively consistent and accurate conditions, which a developing bowler may not be able to

provide. The widely acknowledged role that perceptual skill plays in sport has led to a large

increase in research aimed at discovering the best methods to promote perceptual skill

acquisition (Dicks et al., 2008). Several researchers have indeed stressed the importance of

perceptual skills in developing cricket batters (Weissensteiner et al., 2008; Williams &

McRobert, 2008). There is, however, limited research on the most appropriate ways to

42

develop these perceptual skills, which have been proposed to be more closely related to

experience of large volumes of task-specific practice than simply maturation

(Weissensteiner et al., 2008). This notion has been heavily influenced by research into

deliberate practice, where expert performance was traditionally viewed as a direct and

singular function of the time spent in a particular practice (Ericsson, Krampe, & Tesch-

Romer, 1993). For example, with reference to cricket, the number of balls hit by a batter

regardless of practice task constraints. The key phrase in these proposals is ‘task specific’.

Traditionally in cricket, this practice has been provided through the use of ball projection

machines.

However, the use of such tasks has been questioned in recent times, both theoretically,

through experiential knowledge and now empirically. Preliminary evidence demonstrates

the consequences of changing ecological constraints and employing practice designs that

are not representative of the performance context, such as when using ball projection

machines. These machines afford learners opportunities to become perceptually attuned to

ball flight information only, and prevent the use of advanced information sources prior to,

and at ball release (Renshaw et al., 2007). However, due to high ball velocities generated by

fast bowlers during performance, batters often need to attune to variables that exist in

bowlers’ actions prior to ball release which are available in performance environments

(Abernethy & Russell, 1984; Gibson & Adams, 1989; Müller & Abernethy, 2006; Müller et

al., 2006; Weissensteiner et al., 2008). Experiential knowledge demonstrates the

importance of the batter viewing the point of release of the bowler (Weissensteiner et al.,

2009b; Weissensteiner et al., 2008). These critical information sources are not available

under practice task constraints involving ball projection machines. Research suggests that

more prolonged exposure to ball projection machine tasks may have led the skilled batters

to attune to informational variables which were not present in transfer (Croft et al., 2010;

Renshaw et al., 2007).

Future challenges for practice and learning design

Growing in popularity, the use of video simulations for training perceptual skill in sport is

receiving a lot of research attention. The design has typically been used to simulate

opponent’s movements, requiring the participant to react to dynamic situations, usually

following specific instructional constraints (Dicks et al., 2008). With much of the research in

measuring perceptual skill in sport based around questionable experimental designs (as


43

previously discussed), there are still major doubts over the effectiveness of this type of

training set-up. Additionally, much of this research focuses on simple outcome measures,

as opposed to studying emergent movement organisation, with no researchers having yet

examined the practical use of video simulation training in cricket batting (Williams &

McRobert, 2008). From a two-visual system perspective, there is a need to firstly establish

the limitations of these designs, with the possibilities of enhancing affordance perception

being a more realistic objective (see Chapter 3).

The challenge for cricket skill development programmes is also to understand how ball

projection machines might be used in training along with practice against ‘live’ bowlers,

without inducing over-use injuries. Research is needed to establish how current practice

tasks may allow batters to undertake a requisite volume of task-specific practice to develop

perceptual and movement skills (Weissensteiner et al., 2009a; Weissensteiner et al., 2008).

For example, research is needed to highlight how specific information is used under

changing task constraints (e.g., possibilities of affordance perception in video simulations,

or changing ball projection constraints). Initially, research is needed to re-assess the current

methods used in experimentation and practice task designs, to discover benefits and

limitations of these task designs (Chapter 3), before providing a theoretically principled

approach for future work (Chapter 4 and 5).

2.10. Summary and conclusions

The integration of theoretical and methodological ideals outlined can be exemplified in

dynamic interceptive actions such as cricket batting, as they provide rich environments for

the functional coupling of perception and action, the synergetic relationship between

performer and environment, and demonstrate the importance of representative

experimental task design (Davids et al., 2005; Dicks et al., 2008). Research in cricket batting

has focussed on visual anticipation, reaction times and perceptual decision making (Adams

& Gibson, 1989; McLeod, 1987; Penrose & Roach, 1995), visual tracking and brain

functioning (Land & McLeod, 2000; Taliep et al., 2008), and kinematic and kinetic factors

(Stretch et al., 1998; Taliep et al., 2007; Weissensteiner et al., 2009a). Critically, the

methods used may have failed to provide experimental task designs that are representative

of a performance context, or provide constraints to encompass perception and action

processes. As a result, our current understandings of perceptual and technical factors of

expertise (and how learners develop them) in dynamic interceptive actions in sport may be

44

limited, biased, or even misleading. The use of an ecological framework, underpinned by

knowledge from contemporary neuroscience (e.g. two visual-systems framework) is

expected to allow for advances in understanding the importance of perception and action

contributions in neurobiological systems, and allow for the design and recognition of more

representative experimental and practice task design in sport (Davids, 2008). Research is

also needed to demonstrate the functionality and adaptability of performers under

changing experimental task constraints, and provide theoretical and empirical support for

practice and learning design.

45

“That which can be asserted without evidence, can be dismissed without evidence.”

Christopher Hitchens (1949-2011)

Chapter 3 – Representative experimental and practice design

47

Chapter 3 – Representative experimental and practice task design in

dynamic interceptive actions

Based on the review of literature at the beginning of this candidature process (Chapter 2), it

was surmised that many experimental designs in sports research may have been

compromised by the use of non-representative experimental designs; with research

tending to favour ball projection machines and video simulations. There was a need to

progress our understanding of the difference in movement organisation under changing

task constraints, and assess if life-size video simulations may be used to provide

representative situations for affordance perception or movement regulation after ball

release.

This chapter is based on the following peer-reviewed article:



Perception & Psychophysics, 73, 1242-1254.

Some preliminary results of this work were used in the following book chapter (see

Appendix):



Practice: A Constraints-Led Approach. London: Routledge

48

3.1. Abstract

Movement organisation of cricket batters’ actions were analysed under three distinct

experimental task constraints: a representative condition of a practice context when

batting against a ‘live’ bowler, a ball projection machine and a near life-size video

simulation of a bowler. Results showed that each distinct set of task constraints led to

significant variations in patterns of movement control. Removal of advanced information

sources from a bowler’s action when facing the ball projection machine caused significant

delays in movement initiation, resulting in reduced peak bat swing velocities and a

reduction in quality of bat-ball contact when compared with batting against a ‘live’ bowler.

When responding to a two dimensional video simulation, batters were able to use

information from the bowler’s action to enable fidelity of initial behavioural responses

consistent with the task of batting against a ‘live’ bowler. However, without interceptive

task requirements or actual ball flight information, significant variations in downswing

initiation timing and peak bat velocities were demonstrated. Findings stress the need for

representative experimental and learning designs in fast ball sports for developing

performers.


49

3.2. Introduction

Interceptive actions have been used as highly effective task vehicles for developing

theoretical understanding of the synergetic relationship of information and movement

under severe time constraints (e.g., Caljouw et al., 2004; Le Runigo et al., 2005; Montagne,

Laurent, Durey, & Bootsma, 1999). Temporal demands in fast ball sports often exceed the

intrinsic limitations in visuo-motor delays and movement times (van der Kamp et al., 2008),

as exemplified by the margin for error in the interceptive timing of a cricket batting stroke

reported to be in the region of 2.5 ms (Regan, 1997). To cope with such task constraints,

skilled performers are able to use perceptual information to produce extremely high levels

of precision. Consequently, there has been a significant increase in research examining

perceptual-motor skill in fast ball sports, particularly in assessing visual anticipation. In this

respect, performers consistently show an ability to use advanced kinematic information

from the actions of opponents (e.g., Abernethy & Zawi, 2007; Jackson & Morgan, 2007;

Müller & Abernethy, 2006; Renshaw & Fairweather, 2000), and early ball flight information

(e.g., Land & McLeod, 2000; Müller et al., 2009) to guide their actions.

However, a major concern of typical studies of perceptual-motor expertise has been the

neglect of the role of the environment, aligning with similar limitations in psychological

science (see Brunswik, 1956; Davids, 2008; Davids et al., 2006; Dhami et al., 2004;

Dunwoody, 2006; Hammond & Stewart, 2001b). This concern was epitomized by Egon

Brunswik (1956) over half a century ago when outlining the concept of representative

design, and emphasising the importance of organism-environment relations in the study of

human behaviour. On the whole, Brunswikian concepts still have not been integrated into

psychological research (Rogers, 2008), with researchers traditionally opting for systematic

designs for experimental control, jeopardizing the generalizability of research findings

(Araújo et al., 2007). Generalizability is central to the ideals of Brunswik’s (1956) notion of

representative experimental design, which proposes that experimental stimuli must be

sampled from an organism’s natural environment so as to be representative of the stimuli

to which it is adapted and to which experimental data are intended to be generalized

(Brunswik, 1956). Brunswikian concepts are harmonious with tenets of Gibson’s (1979)

theory of direct perception which emphasized the reciprocal relations between processes

of perception and action in organism-environment interactions. In studies of sport,

representative design supports the need for the generalization of task constraints in

experiments to the task constraints encountered during different performance contexts, for

50

example when perceiving the actions of a ‘live’ opponent in a study of anticipation (Araújo

et al., 2006; Davids, 2008).

Previous research on perceptual-motor skill in sport has been criticised for failing to

maintain the functional coupling of perception and action processes in experimental

designs (e.g., Dicks et al., 2008; van der Kamp et al., 2008). Some studies of perception and

action have demonstrated significant differences in visuo-motor behaviours observed

between laboratory conditions and task conditions representative of performance contexts

(e.g., video simulation versus in situ tasks; see Dicks, Button, et al., 2010; D. T. Y. Mann et

al., 2007). Specifically, limitations of the ubiquitous occlusion and video simulation

methodologies have been attributed to the removal of key sources of information in

experimental design, and a failure to ensure that neuroscientific knowledge of visual

system functioning underpins research designs (e.g., Davids, 2008; van der Kamp et al.,

2008). Traditionally, experimental designs have not ensured that selected task constraints

support the use of functional information-movement couplings. That is, environmental

information presented in experimental tasks, and the action responses required (e.g.,

verbal, written or simplified movements) do not allow performers to replicate the same

perception and action processes as those displayed in representative performance

environments. Research has typically been focused on substantiating expertise effects

rather than comparing participant movement behaviours across varying task constraints. As

a result, research needs to develop a principled theoretical rationale for this line of work to

provide a comprehensive framework to guide future experimentation on perceptual-motor

performance in sport (see Chapters 4 & 5. Also see Pinder, Davids, et al., 2011b; Pinder,

Renshaw, et al., 2011). The integration of Brunswikian and Gibsonian ideas proposes that in

order to attain representative experimental design, experimental tasks need to allow

participants opportunities to pick up and use specifying information from the environment

to support functional movement responses (i.e. perception-action coupling; for an overview

see Warren, 2006).

In spite of the widely-stressed importance of perceptual skills in fast ball sports (Abernethy

& Zawi, 2007; Shim et al., 2006; Weissensteiner et al., 2008; Williams & McRobert, 2008),

much research has analysed performers’ responses in typical performance environments

using ball projection machines to enhance experimental control of projectile trajectories.

For example, in studies of cricket batting, ball projection machines have been used in

experiments to assess gaze behaviours (Croft et al., 2010; Land & McLeod, 2000), visual


51

function (D. L. Mann et al., 2007) and movement organization (primarily temporal

responses between skill levels: Weissensteiner et al., 2009a). However, the use of ball

projection machines (with velocities ranging between 26-30 m·s-1) has revealed significant

differences in spatio-temporal responses of performers (skilled and experienced to less-

skilled and developmental juniors) when compared to facing a ‘live’ bowler projecting a ball

at the same speed (Gibson & Adams, 1989; Pinder et al., 2009; Renshaw et al., 2007). These

findings are consistent with data observed in the use of such machines in other sports (e.g.,

tennis: Shim et al., 2005).

Therefore, current understanding in perceptual-motor expertise in sport (in both visual

perception and technique analysis) may have been compromised through use of

experimental designs which are not representative of performance contexts (i.e., facing a

‘live’ bowler). Not only is this a critical concern for perceptual-motor research, but it also

has major consequences for learning and practice design in fast ball sports, where the use

of ball machines is ubiquitous, particularly in skill development programmes for junior

performers. During learning, performers attempt to converge on useful perceptual

variables to support action in specific performance environments (e.g., perceptual

attunement: Fajen et al., 2009; Gibson, 1966; Jacobs & Michaels, 2002). Intuitively, the

removal of critical perceptual information sources (particularly during early learning or

important developmental stages) may limit the development of performers’ ability to

detect reliable information to support action (e.g., the creation of information-movement

couplings and their refinement over time) (Araújo, 2007; Davids et al., 2005; Jacobs &

Michaels, 2002). Changing the informational constraints on action might result in less

representative practice designs, and changes to a performer’s acquisition of functional

movement control. This idea has been exemplified in cricket batting research, where

Stretch and colleagues (1998) demonstrated that batters adapted spatio-temporal

characteristics of emergent action when facing a ‘live’ opponent, depending on the

required shot response to different bowling trajectories through the pickup of advanced

kinematic information and early ball flight. These adaptations to action ensured that

batters contacted the ball at the right time with the correct spatial orientation (Savelsbergh

& Bootsma, 1994). As a result, when facing a ‘live’ bowler, experienced batters executed

attacking drives which reached peak horizontal velocity 0.02 s before bat-ball contact

(Stretch et al., 1998); consistent with findings in other fast ball sports (e.g., baseball,

McIntyre & Pfautsch, 1982; softball, Messier & Owen, 1984; golf, Shibayama & Ebashi,

1983). Despite these findings, very little work has focused on how differing spatio-temporal

52

responses under varying task constraints affect batting performance outcomes or bat

velocity (force control), beyond simple performance measures (e.g., see Mann et al., 2010).

Clearly, further work is needed to compare perceptual-motor organisation when batting

against a ‘live’ performer and against ball projection machines to observe how advance

kinematic information from a bowler’s actions shapes behaviour.

In one exception, Taliep and colleagues (2007) compared kinematic variables of

performance by skilled and less-skilled cricket batters when completing ‘shadow’ front foot

drives (an attacking shot) against ‘realistic projected video footage’ in a screened simulation

of the performance environment. However, since no comparative studies of movement

behaviour under video simulation conditions and a representative task of batting against a

‘live’ opponent currently exist, it is not understood whether life-size video simulations

provide a representative task for batters. This lack of clarity is mainly due to the removal of

the interceptive action in many simulation designs (e.g., decoupling of perception and

action), and to previous research showing differences in information pick up from 2D video

displays compared to natural performance environments (see Dicks, Button, et al., 2010).

Furthermore, without knowledge of the manipulation of ball length in previous studies

(varying perceptual information and ball trajectories), it is unknown if batters can attune to

small but critical changes in delivery characteristics (e.g., between two different ball landing

positions), when that information is presented in video simulations. Critical information

may be removed completely (e.g., removal of a bowler’s movements when using ball

projection machines), but it may also be present but much harder to detect in a 2D display

than in the natural performance environment.

To assess the degree of association between behaviour under different task constraints, the

fidelity of the action response can be assessed by measuring task performance in detail

(Araújo et al., 2007; Stoffregen et al., 2003; also see, van der Kamp et al., 2008). Therefore,

the aims of the current study were to compare spatio-temporal movement organisation,

bat velocity and interceptive ability (quality of bat-ball contact between interceptive

conditions, see: Müller & Abernethy, 2008) of cricket batters across three distinct tasks

typically used in experimental and learning design. For this purpose, movement

organisation of cricket batters’ actions when performing an attacking and a defensive shot

was compared under three distinct experimental task constraints against: (i) a ‘live’ bowler,

(ii) a ball projection machine, and (iii), a near life-size, 2D video simulation of the same

bowler delivering a ball. It was predicted that spatio-temporal responses when batting


53

against a ‘live’ bowler would differ markedly with performance in both the ball projection

machine and video simulation constraints, with these conditions varying the degree to

which the movement responses and available information are representative of the

performance environment. It was also predicted that bat velocity would differ significantly

under video simulation conditions, with lower peak velocities observed with the removal of

the interceptive task requirement and ball flight information which has been shown to

change prospective movement control (Montagne, 2005; Müller et al., 2009). Furthermore,

analyses of attacking and defensive shots were expected to reveal further insights into the

process of coupling of movement to information in a dynamic interceptive action. These

analyses were expected to demonstrate possible consequences for movement organization

of employing ball projection machines in research and learning designs which remove

advance kinematic (i.e. pre-ball release) information from the bowler’s actions (e.g., see

Weissensteiner et al., 2009a).

3.3. Method

Participants

Twelve cricket batters (mean age: 15.6 ± 0.7 years), with 6.6 ± 0.6 years of competitive

junior cricket experience were recruited for the study. All participants provided informed

consent and ethical clearance was completed through a university ethics committee. Four

left-arm bowlers (mean age = 15.0 ± 0.8 years) with similar conventional bowling actions

(ACB, 1998) and physical attributes (mean peak height of ball release = 2.06 ± 0.07 m; mean

bowling speed = 28.14 ± 0.56 m·s-1) were also recruited for the study. Peak height of release

was measured from a sagittal view of the bowling line. Peak height (i.e. maximum height of

the bowling hand) was used to allow for calculation of a near life-size projection image (see

below). All bowlers were appropriately matched to the batters’ performance level and

experience. Bowling speed was assessed for the four bowlers using a sports radar gun

(Stalker Radar, Texas).

Procedure

Performance observations occurred in the participants’ regular indoor practice facility.

Participants undertook three distinct experimental tasks – batting against; i) a ‘live’ bowler,

ii) a ball machine, and iii), a video simulation, in a fully counterbalanced design to control

54

for order and learning effects. None of the twelve participants had previously faced any of

the four bowlers but had faced bowlers of similar speed and ability in training. All

participants had some limited experience of batting against a ball machine (< 30 trials per

week during years of competitive experience); however, none had any experience of video-

based simulation training. Two weeks prior to data collection, all participants completed six

blocks of six trials (6 cricket ‘overs’ resulting in 36 trials) of ‘simulated batting’ against the

video-based simulation, which allowed participants to become familiarized with equipment

and trial procedures. These trials were completed against footage of different bowlers of

similar ability to those used in the data collection phase of the study, to ensure that

findings were not influenced by any possible learning effects caused by exposure to the

specific bowlers’ movements.

The same balls (‘Oz’ bowling machine ball) were used across all conditions (including filming

of the video simulation video trials) to provide consistency of bounce to participants. The

ball machine (Jugs Inc., Tualatin, Oregon) was set to the mean height of release and bowling

speed recorded from the four bowlers to replicate their typical delivery characteristics (e.g.,

bowling trajectory). The same highly experienced Australian level 3 coach operated the ball

machine for all participants, using a typical standardised pre-delivery routine, where the

operator held the ball up for the batter to see before lowering it directly into the ball

machine (see Renshaw et al., 2007; Shim et al., 2005). The time between release from the

operator’s hand and the ball emerging from the machine head (approximately 1 s) was

consistent for all release trajectories. The sound produced by the ball machine also

provided information for batters to predict when the ball would be released (Shim et al.,

2005).

Deliveries were randomized across all conditions. Both front and back foot shots were

included to alleviate any bias in batters’ responses, and to ensure the experimental set-up

did not direct perceptual choices (i.e. limit batters’ choices to just the two shots of interest).

Bowlers followed a randomised script for ball target locations, which was replicated in the

ball machine condition. Importantly, the ball machine allowed for subtle but critical

changes in delivery trajectory prior to the appearance of the ball that were undetectable by

these participants, alleviating the concern that a ball machine provides too much

predictability of ball trajectory characteristics (Gibson & Adams, 1989; Renshaw et al.,

2007).


55

Participants were instructed under all conditions to perform as they would in a match

situation, by attempting to score as many runs as they could while avoiding being bowled.

No further instructions or knowledge of the experimental aims were provided. In the video

simulation conditions, participants were asked to replicate the shot they would play against

a ‘real ball’ in each situation, producing coupled responses to the video footage.

Participants generally faced 36-40 deliveries in each of the interceptive conditions (ball

machine and bowler) to generate the required number of shots for data analysis, in line

with previous empirical research (Stretch et al., 1998). Participants faced 36 randomised

trials under video screen conditions. Two common strokes in cricket (the forward defensive

stroke, and the front foot straight drive) which have been the focus of previous research

(Stretch et al., 1998) were used to assess movement timing and control of action across the

distinct experimental tasks. These strokes are widely considered as basic performance

foundations, with experiential knowledge and empirical research suggesting that with

modifications the forward defensive shot provides the basis for the attacking straight drive

(Stretch et al., 1998; Woolmer, Noakes, & Moffett, 2008). Importantly, the two shots

require the batter to discriminate ball delivery characteristics (i.e., pickup of trajectory

information to determine the pitching location), between a ball which bounces closer to the

batter (2-3 m from the batter’s preparatory position – see Figure 3.1) and affords an

attacking drive, and a ball which pitches further from the batter (4-5 m), requiring a

defensive response.

Video preparation and screen set-up

Required video simulation footage of the four bowlers was filmed (Sony HVR-V1P) from the

batters’ preparatory position at the batting crease in the same indoor facility as the ‘live’

bowler and ball machine conditions. A marking grid on the floor (0.4 x 1 m areas – See

Figure 3.1) in line with the batting stumps, enabled ball pitching location (direction and

distance from the batting stumps) to be recorded for each video trial. Trials were

randomised in a test package (with an equal number of deliveries from each bowler)

requiring the participant to respond with a range of both front and back foot movements

with no prior knowledge of upcoming deliveries. Knowledge of bounce point for each trial

allowed for consistency across all three conditions. Video simulation footage was projected

onto a large screen (2.6 x 3.5 m) situated 3 m from the popping crease (position of

participants’ preparatory stance), allowing an approximate subtended visual angle of 7° and

a virtual distance of 17.7 m. This set up provided a near life-size image of the bowler at the

56

moment of ball-release in accordance with methods in both cricket (Taliep et al., 2007) and

soccer goalkeeping research (Dicks, Button, et al., 2010).

Figure 3.1. Experimental set-up for ‘live’ bowler, ball machine and video simulation conditions,

respectively

Data collection

Two synchronized cameras (Sony HVR-V1P) were used to simultaneously capture

participant movements (located 10 m from the saggital plane of action perpendicular to the

batting crease) and the point of ball release following established set-up procedures

(Bartlett, 2007). Cameras captured at a frame rate of 100 Hz, and a shutter speed of 1/300

s. Calibration was attained using horizontal and vertical references of known distance.

Participants wore full protective equipment (including batting helmets) in all conditions,

and contrasting markers were placed on the top and bottom edges of the bat, and the

proximal phalanx of the 1st and 5th toes (for front and back feet, respectively). These

markers allowed analysis of step lengths and bat swing characteristics, including peak bat

swing height and linear horizontal bat velocity. Pilot work and previous empirical research

(Renshaw et al., 2007; Stretch et al., 1998) have demonstrated that the measured aspects

are suitably planar to allow for this type of analysis; only straight front foot shots (where

the measured aspects of the batter’s action (i.e. step length) remained within the sagittal

plane) were analysed. The assessment of responses outside of this plane was not included

in this programme of work and beyond the scope and analysis of the current project. Key

phases (dependent variables) of the batting action were identified as: i) point of ball

release, ii) initiation of backswing of the bat, iii) initiation of the front foot movement, iv)

initiation of the downswing of the bat, v) placement (planting) of the front foot, and vi)

point of bat-ball contact (see Renshaw et al., 2007; Stretch et al., 1998). Moment of ball

Video screen

Bowler/ Ball Machine

20.12m (pitch length)

17.7m (distance between creases)

3m

Batter

Stumps

Marking grid


57

release was recorded as the first frame after the ball had left either the bowler’s hand (in

‘live’ and video conditions) or the mouth of the ball projection machine. Front foot

movement initiations and placements were defined as the first frame after the foot had

lifted off, or been placed on the ground, respectively. Initiation of backswing and

downswing were identified within the data based on acceleration patterns of the bat end-

point, and confirmed using frame by frame analysis (due to preparatory movements).

Timing of the predicted point of bat-ball contact when facing the video screen was

determined by three high level cricket coaches (English Cricket Board levels 2 and 3), in

accordance with previous work (Taliep et al., 2007). Coaches viewed synchronized video of

the presented video trial, and the batter’s responses and predicted the point at which bat-

ball contact would have occurred. Coaches’ predictions were highly consistent with each

other (within 0.03s), and in line with previous findings (Taliep et al., 2007). The average

frame number provided by the three coaches’ assessments was taken as the point of

predicted bat-ball contact. Two-way (experimental task x shot) repeated-measures analyses

of variance confirmed that there were no significant differences across conditions (F(2,142)

= 0.09, p > .05) or shot type (F(1,71) = 0.02, p > .05) in the timing between release and bat-

ball contact (‘live’ bowler or ball machine) or predicted contact (video simulation).

Dependent measures

Quality of bat-ball contact

A measure of quality of bat-ball contact (QoC), validated by Müller and Abernethy (2008),

was used as a simple but reliable tool for assessing interceptive success under both ‘live’

bowler and ball machine task constraints. A trained observer provided a QoC score for each

trial in line with the validated measure. The scores where defined as: i) ball contacting the

bat and travelling in a direction consistent with the pre-contact plane of bat motion/ swing

(2 points), ii) ball contacting the bat but deflecting in a direction inconsistent with the pre-

contact plane of bat motion/ swing (1 point), and iii), the ball not making contact with the

bat (0 points). Reliability was assessed on a selection of 42 trials (10%). Intra-rater reliability

was assessed by comparing two video reviews (with a four-week break) of the first

observer, while inter-rater reliability was assessed by comparing scores of the first observer

with those of a second observer. Strong correlations were found for both intra- (rs =.87) and

inter-rater reliability (rs=.86), consistent with previous work (Mann et al., 2010).

58

Temporal Phasing

For each condition, means and standard deviations of movement timing data (s) were

recorded for each of the key initiation points relative to ball release. Unless stated, data

were calculated in seconds (mean ± standard deviation) before bat-ball contact (or

predicted contact), with point of ball release occurring 0.64s before bat-ball contact.

Bat velocity, peak bat swing height and step length

Trials were analysed using SIMI motion software (SIMI Reality Motion Systems GmbH). Data

were smoothed using a 4th order Butterworth recursive filter with a cut-off frequency of

4.5 Hz. Coordinates of the digitizing process were used to calculate linear horizontal

velocity of the bat throughout the action, peak height of the bat swing, and step length at

bat-ball (or predicted) contact. Bat swing height was recorded as the peak height attained

throughout the batter’s action, and step length was measured between foot markers at the

moment of bat-ball (or predicted) contact. Digitizer accuracy was assessed using the

Intraclass correlation coefficient for both intra- (ICC = 0.96) and inter-rater (ICC = 0.94)

reliability measures, considered to demonstrate high to excellent reliability within the

relevant literature (Atkinson & Nevill, 1998; see also Vincent, 1994).

Data analysis

Video trials used for analysis were initially evaluated to ensure consistency of responses

and delivery characteristics (ball bounce location) across all three conditions. In line with

similar work (Shim et al., 2005), trials demonstrated that participants did not pre-empt the

ball machine delivery, nor did they make early movements forwards or backwards and have

to correct their original decision. Six forward defensive and six forward drive shots were

analysed for each participant in each condition, resulting in a total of 422 trials (12

participants x 3 experimental tasks x 2 shot responses x 6 trials). Separate two-way

(experimental task x shot) within-subject analyses of variance (ANOVAs) with repeated-

measures on both factors were used to analyse the data on all dependent measures. In

cases of violation of the sphericity assumption, a Greenhouse-Geisser correction (based on

epsilon values of less than .75) was used to adjust the degrees of freedom for treatment

and error terms of the repeated measures variables in the ANOVAs. This protocol was


59

followed throughout all experimental Chapters and in accordance with recommendations

by Field (2009). Following these analyses, Post-hoc pairwise comparisons were undertaken

to assess which comparisons were statistically significant in each instance. Paired t-tests

were used to assess differences across experimental task for both shot types. Bonferroni

adjustments were used in all cases to control for type I error (Field, 2009) resulting from

any inter-dependence within dependent measures. Finally, Partial eta squared (ηp2) values

were provided for each ANOVA to provide an indication of the effect size for each factor or

interaction of factors.

3.4. Results

Quality of bat-ball contact

The analysis of variance for QoC scores (‘live’ bowler versus ball machine - see Figure 3.2)

revealed main effects for both experimental task (F(1,71) = 31.76. p < .01, ηp2 = .31) and

shot type (F(1,71) = 14.99, p < .01, ηp2 = .17), with significantly higher scores under ‘live’

bowler task constraints (p < .01), and when responding with a forward drive (p < .05).

Figure 3.2. Mean group batting quality of contact (QoC) scores across interceptive experimental task

constraints (B, BM) and shot type. Data are represented with standard errors. *Significant

differences between experimental task constraints (p < .01); + Significant differences in scores

collapsed across experimental condition for shot type (p < .05); Δ Experimental task-specific

differences for drive and defensive shots (p < .05).

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Drive Defence

Qua

lity o

f con

tact

Bowler

Ball Machine

*

*Δ

Δ

+

60

Front foot movement

Front foot movement characteristics were significantly shaped by experimental task

constraints (comparison of all three conditions - see Figures 3.3 and 3.5). There was a main

effect for experimental task on the timing of front foot initiation (F(2, 142) = 67.92, p < .01,

ηp2 = .49), primarily due to a significant delay when under ball machine constraints, for both

drive (p < .01) and defence (p < .01) shots. Similarly, main effects for both experimental task

constraints (F(2,142) = 26.13, p < .01, ηp2 = .27) and shot type (F(1, 71) = 7.75, p < .01, ηp

2 =

.10) were found for the timing of front foot placement, with later (i.e., closer to bat-ball

contact) placements occurring under ball machine task constraints (p < .05), and when

performing a forward drive (p < .01).

There were significant main effects for both experimental task constraints (F(2, 142) = 7.35,

p < .01, ηp2 = .09) and shot type (F(1, 71) = 182.69, p < .01, ηp

2 = .72) for batters’ front foot

step lengths (see Figure 3.5), which were shorter under ball machine task constraints (p <

.01), and when performing forward defensive shots (p < .01).

Figure 3.3. Differences in the timing and initiation of front foot movement (FFM) and front foot

placement (FFP) relative to bat-ball contact, when facing three distinct experimental tasks.

*Significant differences between experimental task constraints (p < .05); **Significant differences

between experimental task constraints (p < .01); + Significant differences in scores collapsed across

experimental condition for shot type (p < .01).

0.00

0.10

0.20

0.30

0.40

0.50

0.60

FFM FFP

Tim

e be

fore

bat

-bal

l con

tact

(s)

Drive

FFM FFP

Defence

BowlerBall MachineVideo Screen

**

*

**

*

+


61

Bat swing

A significant main effect revealed that backswing initiation time was affected by

experimental task constraints (F(2,130) = 67.33, p < .01, ηp2 = .51), primarily due to

backswing initiation occurring significantly later against the ball projection machine when

compared to both the ‘live’ bowler and the video simulation conditions (see Figure 3.4: p <

.01). Similarly, main effects for both experimental task (F(2,142) = 26.26, p < .01, ηp2 = .27)

and shot type (F(1,71) = 80.54, p < .01, ηp2 = .53) demonstrated that experimental task

design influenced the timing of the downswing initiation. There were significant differences

in timing of downswing initiation when facing the ball machine compared with both the

‘live’ bowler (p < .01), and video simulation task constraints (p < .05). In contrast with

observations on backswing initiation, there were also differences in the timing of

downswing initiation between the ‘live’ bowler and video simulation constraints, with

initiation occurring significantly earlier when facing a video screen (p < .01). Additionally,

the downswing was initiated significantly later (see Figure 3.4) under all three experimental

task constraints when using an attacking shot (0.18 ± 0.05 s) compared to a defensive shot

(0.22 ± 0.06 s).

Figure 3.4. Differences in the timing and initiation of backswing (BS) and downswing (DS) relative to

bat-ball contact, when facing three distinct experimental tasks. *Significant differences between

experimental task constraints (p < .05); **Significant differences between experimental task

constraints (p < .01); + Significant differences in scores collapsed across experimental condition for

shot type (p < .01).

There were significant main effects for both experimental task constraints (F(2, 130) =

14.78, p < .01, ηp2 = .19) and shot type (F(1, 65) = 138.95, p < .01, ηp

2 = .68) on peak back

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

BS DS

Tim

e be

fore

bat

-bal

l con

tact

(s)

Drive

BS DS

Defence

BowlerBall MachineVideo Screen

**

* ***

**

* * **

+

62

swing height attained by participants (see Figure 3.5). Post-hoc analysis revealed that

significantly shorter backswing heights were attained when facing a ball machine, than in

the ‘live’ bowler (p < .01) or video simulation tasks (p < .01). Analysis also revealed a

significant difference between shot type and peak backswing height, with batters

demonstrating higher peak backswings when using an attacking shot (p < .01).

Figure 3.5. Mean group differences in peak backswing heights (above left) and step lengths (above

right) during an attacking and defensive shot under three distinct experimental task constraints

(error bars represent standard deviation). *Significant differences between experimental task

constraints (p < .01); + Significant differences in scores collapsed across experimental condition for

shot type (p < .01).

Bat speed

Table 3.1 summarizes the mean group data for the peak horizontal velocity attained during

the batter’s action, and the time during the downswing at which the peak velocity

occurred, relative to bat-ball (or predicted) contact. There were significant main effects for

peak horizontal velocity of the bat end-point for experimental task constraints (F(2,142) =

37.18, p < .01, ηp2 = .34) and shot type (F(1,71) = 870.46, p < .01, ηp

2 = .93). Batters achieved

higher peak bat velocities when batting against a ‘live’ bowler than both ball machine and

video screen conditions (p < .01). There was also a significant interaction between

experimental task constraints and shot type (F(2,142) = 13.39, p < .01, ηp2 = .16),

predominantly due to the significant decrease in mean peak horizontal velocity for the

forward defensive shot under video simulation conditions (p < .01). Furthermore, significant

main effects were found for the timing of peak velocity across both experimental task

constraints (F(2,142) = 33.41, p < .01, ηp2 = .66), and shot type (F(1,71) = 136.09, p < .01, ηp

2

+

0.80

0.90

1.00

1.10

1.20

1.30

1.40

1.50

1.60

1.70

Drive Defence

Peak

hei

ght o

f the

bac

ksw

ing (

m)

0.50

0.60

0.70

0.80

0.90

1.00

1.10

Drive Defence

Step

Leng

th (m

)

*

Bowler Video Screen Ball Machine

**

*

+


63

= .32), with higher peak velocities when facing a ‘live’ bowler compared to both ball

machine and video simulation conditions (p < .01), and when responding with a drive shot

(p < .01). Significant differences in timing of peak bat swing were found between batting

under video simulation conditions for both the drive and defence when compared with

both ‘live’ bowler (p < .01) and ball machine task (p < .01). Results displayed a significant

interaction between experimental task constraints and shot type (F(2, 142) = 7.91, p < .05,

ηp2 = .10). Figure 3.6 displays the grouped mean horizontal bat velocity for the forward

drive. Note that the time at which peak velocity occurred relative to bat-ball (or predicted)

contact indicates not only the different peaks across the experimental tasks, but also a

dissimilar curve shape for the bat end-point velocity in the video simulation task due to the

removal of the bat-ball contact.

Table 3.1. Peak horizontal bat end-point velocity (m·s-1), and time (s) at which peak velocity occurred

relative to bat-ball or predicted bat-ball point of contact, for forward drive and forward defensive

shots.

Peak bat velocity Timing of peak velocity

Drive Defence Drive Defence

M SD M SD M SD M SD

Bowler 11.38 1.75 7.37 1.45 -0.01 0.02 -0.03 0.02

Ball Projection Machine 10.62 1.89 7.32 1.37 -0.02 0.02 -0.03 0.01

Video Screen 10.31 1.82 5.25 1.71 0.01 0.02 -0.02 0.03

64

Figure 3.6. Mean group horizontal bat end-point velocities for the forward drive shot across three

distinct experimental tasks (N.B. Data peaks do not align with analysed data in Table 3.1 due to peak

horizontal velocities occurring at differing times across all trials).

3.5. Discussion

The design of experimental task constraints that effectively capture organism-environment

relationships remains a prominent concern in experimental psychology (Brunswik, 1956;

Dhami et al., 2004; Dunwoody, 2006; Rogers, 2008). This study provided evidence to

support current concerns expressed by perceptual-motor behaviour researchers over the

generality of performance data from experimental and learning tasks to performance

contexts, such as sport (cf. Dicks, Button, et al., 2010; van der Kamp et al., 2008). Data

revealed significant changes in timing and organisation of junior cricket batters’ movements

under different task constraints. These findings have major implications for learning design

at these important developmental stages of learning in ball sports like cricket, particularly

due to the heavy use of ball projection machines in many training programmes.

‘Live’ bowler-ball projection machine comparisons

The most pronounced differences observed in the data demonstrated that even simple

performance measures, such as QoC and bat swing velocities, are significantly affected by

the removal of key sources of perceptual information. Batters demonstrated definitive

-2

0

2

4

6

8

10

12

-0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2

Grou

p m

ean

horiz

onta

l bat

end

-poi

nt v

eloc

ity

(m·s-1

)

Time (s)

Bowler

Ball Machine

Video Screen


65

movement initiation effects (backswing and front foot) shortly after ball release when

facing a ‘live’ bowler. These data provided evidence for the use of advance sources of

information to organise movement patterns, available from the kinematics of the bowlers’

actions (see Shim et al., 2005; Shim et al., 2006). This observation was particularly evident

when considering that the batters needed to complete one of two fundamentally different

tasks: that is, making a definitive movement forwards (for the drive or the defence) or

backwards (against shorter pitching trials). Due to subtle changes of the ball projection

machine head between trials (allowing us to randomise angle of delivery and therefore

pitching length), batters in this study were unaware of upcoming delivery characteristics in

advance, a concern with previous research involving ball projection machines (Gibson &

Adams, 1989; Renshaw et al., 2007). The use of perceptual information from the bowler’s

actions allowed batters to significantly increase peak bat swing heights and step lengths

(see Figure 3.5), similar to findings from previous research in which tennis players were

observed to use advance information sources from an opponent’s actions to increase their

court movement coverage by up to 1.2m (Shim et al., 2005). Importantly, the finding that

batters displayed lower backswing heights and shorter step lengths when completing a

forward defence, compared to the forward drive, supports previous work (Stretch et al.,

1998). This observation confirms that the batters were able to decide on the required

stroke before the downswing began, based on advance kinematic and early ball flight

information. Comparatively, similar variations in movement responses were observed when

batting against a ball projection machine, even with the removal of pre-release information

sources from the bowler, albeit occurring significantly later. Significant delays in backswing

and front foot movement initiation times of 80 and 100 ms, respectively, required batters

to functionally adapt their actions (implement lower peak bat swing heights and shorter

step lengths - see Figure 3.5) to ensure a degree of task success. However, batters

demonstrated significantly lower performance scores (QoC – see Figure 3.2) and lower peak

bat swing velocities (10.62 versus 11.38 m·s-1) when compared with batting against a ‘live’

bowler. Batters attained peak bat velocities just before the point of bat-ball contact (-0.02s)

under both interceptive task conditions (Stretch et al., 1998), demonstrating the use of

prospective information from ball flight characteristics for the timing of interception.

Prospective information is information about the current future, that is, the performer is

informed about the future outcomes if the current state is maintained (Montagne, Bastin,

& Jacobs, 2008); hence, it provides information for the modification of movement, allowing

performers to adapt behaviour independently of specific task constraints. However, critical

delays in movement timing imposed by the task constraints (through removal of key

66

perceptual information) could not be offset by the batters prospectively controlling spatio-

temporal characteristics of the action based on ball flight information alone. Interestingly,

the strong within-task relationships between time of downswing initiation and point of bat-

ball contact suggested that the changes in timing of downswing initiation were caused by

differences in the information available between tasks. For example, the batters produced

equally consistent timings for downswing initiations in the ball projection machine

condition, but which occurred significantly later (closer to point of bat-ball contact) than

against a ‘live’ bowler.

The added temporal constraint imposed by the ball machine task constraints in this study

raises concerns over experimental and learning task designs which exclude anticipatory

perceptual sources. It appears that much of the current data on perceptual anticipation

(e.g., gaze behaviours, or movement-based skill differences) is based on experimental

designs that are not representative of human performance contexts such as sport. It is

possible that current data on technical and perceptual characteristic (e.g., visual search)

differences across skill levels in cricket batting (e.g., Land & McLeod, 2000; Weissensteiner

et al., 2009a) may be confounded by the amount of task-specific practice that participants

have been exposed to against ball projection machines in developmental programmes (e.g.,

U15 to adult level programmes). In these programmes some batters may have been

essentially learning a different task to that required in actual performance environments.

‘Live’ bowler-video simulation comparisons

Our results showed that batters were able to achieve the same temporal advantage against

a ‘live’ bowler and video simulation conditions, demonstrating comparable movement

organisation for the critical early movement initiations (i.e., preparatory actions of

backswing and front foot movement). Backswing and front foot movement initiation points

occurred ~60 and 130 ms after ball release, respectively, under both task constraints. This

performance characteristic supported equivalent peak bat swing heights and step lengths

across shot types (see Figure 3.5). Batters were able to pick up and use pre-ball release

information and from the first portion of ball flight, from a ‘live’ bowler and when

presented in a video simulation.

These findings might be considered in light of advances in behavioural neuroscience (visual

system functioning). Requiring batters to couple movements to video-simulated


67

information on a screen enabled comparison with information provided by a ‘live’ bowler.

This methodological advance helped address concerns over speed/accuracy trade-offs (e.g.,

requiring participants to ‘react as quickly as possible’ in tests of perceptual skill) which

seem to have confounded previous studies in visual anticipation (see van der Kamp et al.,

2008). Data from our study demonstrated that junior batters’ perceptions, decision-making

and initial movement responses in this specific video simulation task were representative of

similar processes observed in a ‘live’ bowler condition. Action fidelity was supported, and

performance in one context (initial movements against a video simulation) statistically

corresponded with performance in the other context (e.g., that of a ‘live’ bowler). This

finding, while inconsistent with some previous work comparing in-situ and video-based

designs (e.g., Dicks, Button, et al., 2010), may be attributable to the maintenance of a fully

simulated action (coupled response), rather than a simplified micro-movement reaction

(such as a movement in the anticipated direction). Because of this methodological advance,

the video simulation allowed batters to couple preparatory movements to the pre-release

and early ball-flight information. Many researchers have previously alluded to the

possibility of using video simulation designs to study or train visual anticipation processes

(Abernethy, Wood, & Parks, 1999; Rowe & McKenna, 2001; Williams et al., 2003). Our data

suggest that video simulations may indeed provide representative performance tasks for

assessing (or training) affordance perception in developing athletes. However, it remains

unclear whether this method could result in the same affordance perception (attunement

to subtle but critical changes in response requirements) or efficient and accurate action

production without the requirement for simulated movement performance by participants

(see van der Kamp et al., 2008). An important finding from this experiment is that, when

perception for action is available (under video simulation constraints), it enables a higher

fidelity of the initial simulated action responses than when an interceptive action is

performed without the availability of representative perceptual variables (under ball

machine conditions). These data provide a demonstration of the theoretical role of

affordances in guiding skilled actions, and are a relevant indication for the strategy of

manipulating key task constraints in training sessions. Further work is needed to

understand how the perception of affordances for action may be incorporated into learning

designs in developmental sport programmes.

The most pronounced differences in our batting data provided clear evidence for concerns

over generalising observations between experimental tasks which lack fidelity of

performance characteristics. Changes in the initiation of the downswing and peak bat swing

68

velocities demonstrated a prospective control strategy, with batters’ comparing the

perceived current state of the environment (e.g., time to contact) with the requirements

for successful interception (Fajen et al., 2009; Montagne, 2005). The a priori concern that

two-dimensional simulation displays do not provide sufficient information on ball flight

characteristics to support actions such as interceptions, was vindicated by observations of

significant differences in timing of downswing initiation, and markedly lower peak bat swing

velocities compared to when batting against a ‘live’ bowler. Furthermore, data on the time

at which peak bat swing time was attained by the batters under video simulation conditions

poses some challenges for such experimental designs. For example, in the video simulation

task constraints peak bat velocity occurred after the point at which interception was

predicted to have occurred (see Figure 3.6). Batters were unable to accurately judge

movement requirements without actual ball flight and bounce location information, which

are both important for enhancing the quality of interceptive actions (see Müller et al.,

2009). Batters were either not able to attune to this information, or it could not be

faithfully represented in the 2D video simulation methodology. Our findings offer further

support for previous research demonstrating that the assessment of perceptual-motor

performance using video-based simulation paradigms, particularly when perception and

action are decoupled, can lead to serious errors by participants in judging projectile

interception location (for a collation of assessment studies see van der Kamp et al., 2008).

Additionally, some possible limitations of other methods of assessing interceptive timing

(e.g., comparison with coaches' predictions, Taliep et al., 2007) and possible differences in

the level of experience that batters had in the three distinct conditions in the current study,

should be acknowledged as issues in need of further study.

General discussion

The results of the present study revealed significant differences in performance of

developmental batters between a representative practice task (batting against a ‘live’

bowler), and both video simulation and ball projection machine task constraints,

traditionally used in the assessment of perceptual-motor skill in ball sports. Results

demonstrated that the batters were able to functionally adapt behaviour for each specific

set of task constraints (e.g., the regulation of spatial characteristics under ball machine task

constraints to account for delays in movement initiations). However, the removal of key

perceptual variables to support action (both pre-release, or actual ball flight), suggested

that empiricists should be cautious in interpreting which aspects can be generalised from


69

experimental to performance task constraints (e.g., kinetic and kinematic variables, Taliep

et al., 2007). It is feasible that current popular experimental designs may actually be

limiting progress in understanding and training perceptual and technical abilities of

developmental performers in ball sports. In order to better understand the characteristics

of perceptual-motor skill, and how to develop them, empiricists should attempt to design

experimental task constraints that are representative of specific performance contexts. The

representative task adopted in the present study was that of a normal practice context in

the sport of cricket. Some may argue that differences may exist between observations of

batting performance against a ‘live’ bowler in a different context (e.g., competitive sport).

This concern was beyond the scope of the current study, and is an important question for

future research to assess. Future work should also focus on the assessment of learning

design across various skill levels and temporal constraints (ball speeds), to assess how

informational variables are used at different performance development levels. Indeed, it is

currently unknown if the findings regarding video simulations presented here would also be

observed in groups of highly skilled or senior batters in elite sport programmes, and this is

another aspect which should be investigated in future work. However, there are both

empirical (Renshaw et al., 2007) and experiential reports (Renshaw & Chappell, 2010)

showing similar findings for senior and skilled batters.

The first stage of truly understanding how skilled performance in interceptive actions can

be developed must be to measure and formally describe tasks that adequately capture the

functional behaviour of individuals in a specific performance environment, before posing

questions on how individuals achieve knowledge about that environment (See Chapter 4.

Also see Araújo & Davids, 2009; Fajen et al., 2009; Pinder, Davids, et al., 2011b). The

concept of action fidelity could be used to examine whether a performer’s responses (e.g.,

actions or decisions based on availability of perceptual information) are the same under

various task constraints.

71

“A theory is the more impressive the greater the simplicity of its premises, the more

different kinds of things it relates, and the more extended its area of applicability.”

Albert Einstein (1879-1955)

Chapter 4 – Representative Learning Design in sport

73

Chapter 4 – Representative Learning Design: A theoretical framework

for research and practice design in sport

Following the findings of Chapter 3, it became apparent that many current experimental

and learning designs (e.g., the design of practice tasks) in sport may not adequately

represent the performance setting of interest; despite some previous attempts to highlight

this issue (e.g., Araújo et al., 2007; Dicks et al., 2008). Here, therefore, is a developed

theoretical framework, based on the tenets of Ecological Dynamics to provide a principled

approach for experimental and practice design in sports research and performance.

This chapter is based on the following peer-reviewed journal article:




74

4.1. Abstract

Egon Brunswik proposed the concept of representative design for psychological

experimentation, which has historically been overlooked or confused with another of

Brunswik’s terms, ecological validity. In this article, we reiterate the distinction between

these two important concepts and highlight the relevance of the term representative design

for sports psychology, practice and experimental design. We draw links with ideas on

learning design in the constraints-led approach to motor learning and nonlinear pedagogy.

We propose the adoption of a new term, representative learning design to help sport

scientists, experimental psychologists, and pedagogues recognise the potential application

of Brunswik’s original concepts, and ensure functionality and action fidelity in training and

learning environments.

halla

Due to copyright restrictions, the published version of this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the published version online at: http://eprints.qut.edu.au/47250/

85

Wisden Cricketers’ Almanack (1867)

Chapter 5 – Principles for the use of ball projection machines

87


Further to Chapter 4, the second paper of the theoretical phase of this thesis aimed to

provide a specific and principled theoretical framework to guide future experimental and

practical uses of ball projection technology in sport. Due to the prominence of ball

projection technology in both experimental (Croft et al., 2010; Land & McLeod, 2000;

Weissensteiner et al., 2009a) and learning designs (particularly in developmental

programmes – Woolmer et al., 2008), the purpose of this paper was to provide an overview

of the extant research to date and provide a useful model for both scientists, coaches and

practitioners to guide the future use of such technology.

This chapter is based on the following peer-reviewed journal article:

Pinder, R. A., Renshaw, I., Davids, K., & Kerhervé, H. (2011). Principles for the use of ball

projection machines in elite and developmental sport programmes. Sports Medicine,

41(10), 793-800.

88

5.1. Abstract

Use of ball projection machines in the acquisition of interceptive skill has recently been

questioned. The use of projection machines in developmental and elite fast ball sports

programmes is not a trivial issue, since they play a crucial role in reducing injury incidence

in players and coaches. A compelling challenge for sports science is to provide theoretical

principles to guide how and when projection machines might be used for acquisition of ball

skills and preparation for competition in developmental and elite sport performance

programmes. In this Chapter, we demonstrate how principles from an ecological dynamics

theoretical framework could be adopted by sports scientists, pedagogues and coaches to

underpin the design of interventions, practice and training tasks, including the use of hybrid

video-projection technologies. The assessment of representative learning design during

practice may provide ways to optimise developmental programmes in fast ball sports and

inform the principled use of ball projection machines.


89

5.2. Introduction

Ball projection machines typically play an integral role in practice and training environments

in many sports, from cricket and baseball to volleyball and tennis. Recently, it has emerged

that not all skilled performers agree that the use of projection machines in practice

provides a functional task to practice interceptive actions, leading to some contention

among expert coaches. For example, some high performance and developmental

programmes have taken steps to extensively reduce the use of these machines in the sport

of cricket (Renshaw & Chappell, 2010). Greg Chappell, a former prominent Australian

cricket batsman and head coach of the National Centre of Excellence, now talent

development manager, describes his stance:

“...what my intuition told me for years was that the bowling machine was

a totally different exercise from batting against the bowler. From my own

personal experience of batting against the bowling machine, it wasn’t a

great experience because once I’ve done it a few times I decided that it

wasn’t going to help me with batting. I was better off not to bat at all than

to go and bat on a bowling machine because the activity is so different. [In

an actual cricket match] you know the bowler’s preparation to bowl; you

know everything—all of the cues and clues that you’re getting from the

bowler is really important to get into the rhythm of the bowler and to get

the timing of your movements. You take the bowler out of the equation,

you stick a machine there that spits balls out at you and you’ve lost all

those cues and clues. What I’ve subsequently found is that research is

telling us what my intuition and my experience was telling me. The other

thing is that the research into expertise tells you that experts are better at

picking up the cues and clues than the average player. So why take it away

from everyone and stop them from developing the things that will help

them get better?”

(Renshaw & Chappell, 2010)

Conversely, the late Bob Woolmer, an equally respected and renowned former

international batsman and national coach of South Africa and Pakistan, considered the ball

machine one of the “most essential tools in modern cricket” (Woolmer et al., 2008). One of

90

the primary uses of projection machines in practice seems predicated on movement

repetition (Woolmer et al., 2008) considered traditionally as an essential feature of

‘perfecting’ a putative ‘ideal’ technique in the process of skill acquisition (Gentile, 1972;

Schneider, 1985). This idea is exemplified in the most up-to-date coaching literature on

cricket batting, which discusses the use of ball machines to help ‘groove the skill’ (Woolmer

et al., 2008). Additionally, projection machines allow individuals to achieve a high volume of

practice by facing more balls in a short period of time in order to practice specific actions

hundreds of times. This is not only a critical issue for sports coaches, but a very important

theoretical and methodological one for sport science researchers.

5.3. The problem of practice volume

Projection machines provide relatively consistent and accurate practice conditions, which

developing athletes (e.g., pitchers, bowlers) may not be capable of producing for their

peers. This is important, since skill acquisition in interceptive actions has been associated

with large volumes of task-specific practice (Weissensteiner et al., 2008). However, an over-

reliance on projection machines may have been inadvertently induced by some

perspectives of expertise which have over-emphasised practice volume (e.g., quantity of

balls hit) over the quality of practice task design. Practice volume is central to many

prevalent perspectives on expertise, such as the 10 000 hour rule (Simon & Chase, 1973),

the power-law of practice (Newell & Rosenbloom, 1981), and deliberate practice (Ericsson

et al., 1993). To exemplify, the most comprehensive and relevant coaching literature in

cricket batting proposes that batsmen require “10 000 repetitions of an action or skill to

penetrate the subconscious” and that this conditioning “enables the batsmen to react

instinctively in match conditions” (Woolmer et al., 2008). In complex skilled actions, it is

important to consistently achieve a particular performance outcome; however it has been

demonstrated that skilled movement patterns are rarely repeated in an identical way on

two or more occasions as performance outcomes are achieved (Davids et al., 2008). The

need for ‘repetition without repetition’ in practice has been noted as a critical feature of

successful motor-learning (Bernstein, 1967; Renshaw et al., 2010), with performers using

movement variability and stability paradoxically to influence periods of performance

outcome consistency and movement pattern adaptability (Renshaw et al., 2010). This is

important to note since the ways in which projection machines are currently used appears

to be focused on stability and blocked practice of isolated movement aspects (e.g., blocked

practice of a single type of shot).


91

But how does one practice multi-articular actions for an extended number of trials and for

prolonged periods of time, without placing too much stress on the bodies of coaches,

pitchers or bowlers? The practical benefits of projection machines have been highlighted by

research into overuse injuries in sports relying heavily on multi-articular projecting actions

(e.g., baseball pitching, cricket bowling). A clear advantage gained from using ball

projection machines is that they alleviate the workload required from bowlers or pitchers

during batting practice. This is most important since, in cricket, bowling injuries are heavily

attributed to overuse through high bowling workloads, particularly at developmental stages

(Dennis et al., 2005; Stretch, 2003). Critically, once a player sustains an injury, the likelihood

of re-occurrence is increased (Nuttridge, 2001; Stretch, 2003). Similar findings exist in

baseball, with overuse injuries of the shoulder being a primary concern for developing

performers (Fleisig et al., 2011; Wilk et al., 2011). A recent prospective study demonstrated

that youth athletes pitching more than 100 innings per calendar year were significantly

more likely to sustain injury. To counter the problem of injuries, many coaches in cricket

rely heavily on providing simulated actions such as ‘throw downs’ (over-arm throws from a

reduced distance) to replicate ball flight information and maintain the temporal demand

reminiscent of bowling. However, there is some anecdotal evidence from the coaching

literature of similar levels of overuse injuries in coaches using ‘throw downs’ to simulate

bowling deliveries in cricket (Woolmer et al., 2008). In light of these data it is apparent that

use of projection machines in practice programmes remains important in reducing the risks

of injury incidence.

5.4. Implications for skill acquisition

As well as being perceived as a benefit in reducing injury incidence, ball projection

machines have also been considered useful tools for the acquisition of skilled hitting

actions; allowing a performer to focus on one isolated aspect (e.g., a specific shot or

stroke), practice individually, and complete large volumes of practice in a short period of

time. Despite these reasons, some studies assessing the use of projection machines in

sports performance have questioned their role in athlete preparation, skill acquisition and

assessment. There is clear evidence that use of projection machines in tennis and cricket

creates significant differences in timing and control of performers’ actions, as well as a

reduction in the quality of interception when compared to facing a ‘live’ opponent

delivering a ball with the same characteristics (see Chapter 3; Pinder, Davids, et al., 2011a;

92

Pinder et al., 2009; Renshaw et al., 2007; Shim et al., 2005). In developing junior

performers, especially, these differences are manifested in significant delays in movement

initiation times which increase the temporal demand on the unfolding action. For example,

it has been reported that developing junior cricket batters initiated the backswing of the

bat and front foot movement significantly later when performing front foot shots (e.g.,

moving the front foot towards ball bounce) against a projection machine set to the same

speed (≈28 m·s-1) and with similar trajectory characteristics as a ‘live’ performer (Pinder et

al., 2009). Critically, these delays in movement initiation resulted in a reduction in quality of

contact of the interceptive action, a reduction in bat swing speeds, and significantly shorter

step lengths; the need to place the foot as close to the pitch of the ball in these type of

shots (e.g., minimising the impact of late ball-flight deviation) is a well established cricket

coaching principle. Changing the practice task constraints and using projection machines in

junior cricket batting leads performers to re-organise their actions in attempts to achieve

the required spatial-temporal orientation (Pinder, Davids, et al., 2011a; Savelsbergh &

Bootsma, 1994). Here we argue that differences exist between performance contexts and

training task constraints because the latter are used to simulate the former. Differences

may exist between specific training tasks and competitive match contexts. This is a rich area

for future research to address using the principles we outline below (see section 5.5).

Critically relevant information sources from the competitive performance environment are

not available under practice task constraints involving projection machines. Research

suggests that in their current mode of use, prolonged exposure to projection machine

practice tasks may lead athletes to attune to information sources which are not present

during competitive performance, leading to a predictive rather than prospective control

strategy emerging in learners (Croft et al., 2010; Renshaw et al., 2007). Renshaw and

colleagues (2007) demonstrated that, contrary to data reported for junior performers,

experienced cricket batters initiated the backswing of the bat earlier against a projection

machine than when batting against an experienced medium-paced bowler at the same

bowling speed (≈27 m·s-1) (also see Gibson & Adams, 1989). It has also been demonstrated

recently that highly distinctive visual search patterns are used by experienced cricket

batters when practising with projections machines, since they ‘park’ their gaze at a point on

the anticipated trajectory of the ball before release (Croft et al., 2010). Although it is

intuitive to predict differences between batting performance contexts, no research has yet

compared visual strategies of batters under ball projection machine and ‘live’ bowler task

constraints. The use of a principled framework for these comparisons would support


93

analyses to observe whether differences between the two tasks might emerge (for an

empirical study assessing visual strategies between practice task constraints see Chapter 6).

However, a key point to note is that the use of projection machines reduces the

opportunities for developing batters to attune to subtle and relevant sources of pre-ball

release information from a bowler/pitcher’s movements for differentiating ball trajectory,

speed or ball type variations (e.g., different spin rotations), a critical feature of expertise in

interceptive skill (Müller et al., 2006; Ranganathan & Carlton, 2007; Renshaw &

Fairweather, 2000). This criticism can also be directed at the use of ‘throw downs’ to

simulate bowling deliveries in cricket. For these reasons, Pinder et al. (2009) have cautioned

against an “over-reliance of ball projection machines in developmental programmes”. But it

is important to note that this message should not be interpreted as ‘ball machines should

not be used at all during practice’. Rather, practitioners and sport scientists need to

develop a principled theoretical rationale for their use as a skill enhancement tool in sport,

which is elucidated in section 5.5.

5.5. Principles for Future Work

A compelling challenge for sports science is to understand ‘how’ and ‘when’ projection

machines might be used for acquisition of ball skills and preparation for competition.

Ecological dynamics is a theoretical framework which could underpin a reasoned analysis

for use of ball machines in developmental and elite sport programmes. Ecological dynamics

is predicated on ideas of ecological psychology and dynamical systems theory, with a level

of analysis embedded in the performer-environment relationship (Araújo et al., 2006;

Warren, 2006). This theoretical framework proposes that movement behaviours emerge

from dynamic interactions between neurobiological movement systems and their

performance environments (Davids et al., 2008; Newell, 1986). The interaction between

performer, environmental and task constraints results in the emergence of patterns of

movement behaviour that become stabilised through learning and practice.

A model based on the tenets of ecological dynamics has already been outlined for sport

scientists, coaches, experimental psychologists, and pedagogues, to underpin the design of

training interventions and practice tasks in sport (see Chapter 4; Pinder, Davids, et al.,

2011b). The model was predicated on concepts from ecological dynamics and a nonlinear

pedagogy (see Renshaw et al., 2010 for recent reviews of skill acquisition in sport).

Assessment of ‘representative learning design’ in specific practice tasks allows sport

94

scientists to understand the functionality and limitations of particular training

environments. Understanding representative learning design may provide opportunities to

optimise learning programmes in sport and inform use of performance enhancement tools,

such as projection technology, during practice. To assess representative learning design of

specific tasks, practitioners should consider the functionality of the practice task constraints

in allowing performers to pick up and use information sources representative of the

performance context (e.g., by comparing visual search strategies between projection and

‘live’ bowler/ pitcher situations – see Chapter 6). Since information regulates actions, an

important principle is that the key perception and action processes which are coupled in a

competitive performance environment should be maintained in the design of practice task

constraints. In simulations, the degree of association between practice and performance

contexts should be analysed by considering the fidelity of the performer’s actions (for a

detailed overview see Chapter 4; Pinder, Davids, et al., 2011b), such as by measuring and

comparing movement organisation between the different contexts (see Figure 5.1).


95

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96

Principles of representative learning design are summarised in Figure 5.1. The use of

projection machines should be considered in light of ways in which they might alter

learners’ emergent spatio-temporal responses, movement coordination and visual search

behaviours, when compared to facing a real bowler during performance. Future research is

needed to explore ways to increase the functionality of current practice tasks involving ball

projection machines. For example, it was recently reported that a specific ‘near life-size’

video simulation task which maintained a coupling between perception and action

processes, allowed the action fidelity of cricket batters’ preparatory and initial movement

responses to be maintained when compared to facing a ‘live’ bowler (see Chapter 3; Pinder,

Davids, et al., 2011a). Recent technological advances, which combine both video and ball

projection machines (e.g., ‘ProBatter’ – ProBatter Sports, LLC), may have a significant future

in elite sport and development programmes.

However, caution is needed with these new technologies, and the assessment of their

representative learning design may help identify the benefits and limitations of these

hybrid training tasks. As discussed, Croft et al. (2010) found that against projection

machines experienced batters fixated their gaze at a point on the anticipated trajectory of

the ball from the machine. As ‘ProBatter’ systems release the ball from a specific position (a

screen with one hole), it needs to be verified whether the pickup and use of information in

that simulation task actually replicates the competitive performance context. Because of

the high current cost of high fidelity ball projection systems, the standard projection

machine is likely to remain prominent in development programmes for some time. For this

reason, researchers should focus on carefully assessing and designing the informational

properties of a competitive performance environment that might be replicated at different

development and skill levels. This level of analysis is needed to provide insights into the

nature of the transfer of interceptive actions performed against projection machines and

real bowlers, for instance when comparing visual search strategies under both task

constraints (see Chapter 6).

5.6. A future role for ball projection machines?

The relevance of projection machines as part of training programmes needs careful

consideration. The key issue is how best to use them during practice. Current research does

not advocate removal of ball projection machines from cricket training programmes, since

investigation of their use is still in its infancy. Research has not yet examined their role in


97

high and low ball delivery speeds or looked at their effect on timing and coordination in

back foot shots (where a cricket batter moves backwards from their initial position to

intercept a ball which bounces closer to the bowler and reaches the batter around or above

waist height).

An important challenge is to examine their role in developing interceptive actions in early

and more advanced learners in ball sports. In the very early stages of learning when the

focus should be on the construction of a basic coordination pattern from all the possible

degrees of freedom, it is expected that the stable and consistent practice conditions would

greatly benefit the rate of learning (Schöllhorn, Mayer-Kress, Newell, & Michelbrink, 2009)

(also see Davids et al., 2008 for a review). To exemplify this in cricket batting, ball

projection machines could be used to deliver the ball to a restricted spatial location so that

learners stabilise a functional stroke, such as a forward defensive or straight drive.

Developing athletes, in particular, need to be provided with opportunities to establish

functional and stable relationships between perception of information from the

performance environment and their movements (Davids et al., 2008; Newell, 1985).

However, later in learning it is clear that stability and variability of practice task constraints

may allow for the development of more adaptable performers (Renshaw, Davids, Phillips, &

Kerhervé, 2011). At later stages of learning, ball projection machines could be used to

locate the learner in a meta-stable region of a perceptual-motor workspace. In this region,

learners remain in a state of relative coordination with the practice environment, being

unable to function completely independently, nor dependently, on environmental

information to regulate their actions. In the meta-stable region, functional movement

solutions can emerge during task performance, for instance when learners need to decide

whether to move forward or backward in playing cricket batting strokes (see Chapter 7 for

an exploratory investigation into the emergence of a meta-stable performance region in a

representative interceptive cricket action). By accurately projecting the ball onto specific

locations of the cricket pitch, more advanced learners can be forced to enter a meta-stable

region of batting performance to enrich performance during practice (see Hristovski,

Davids, & Araújo, 2009 for an example in boxing). These theoretical ideas imply that

traditional blocked practice methods utilising ball projection technology may prevent more

advanced learners from harnessing motor system degeneracy to functionally adapt stable

patterns of movement organisation, and may actually be dysfunctional when transferring to

more dynamic performance contexts (Kauffmann, 1995).

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As a principle, therefore, it seems that, at all stages of learning, the role of projection

machines may be to ‘supplement’ rather than ‘replace’ the role of the ‘live’ bowler in the

acquisition of batting actions. Ensuring a balance between the use of projection machines

and bowlers may also ensure that batters are able to constantly attune and recalibrate

(recognise and adjust) to differences in ball flight characteristics under the distinct practice

contexts and establish important information-movement couplings. However, further

research is needed to assess the effects on skill acquisition of different volumes (amount of

time) of supplementary practice in fast ball sports (e.g., visual training through video

simulation designs or ball projection machines).

Additionally, variations in ball speed and trajectories (e.g., constant changes in bounce

location) may allow increased opportunities for batters to exploit and master the

perceptual degrees of freedom which support adaptive movement behaviours needed

during performance (see Savelsbergh, van der Kamp, Oudejans, & Scott, 2004). Intuitively,

it would be predicted that when there is a reduced temporal constraint on batters’ actions,

such as when playing against slow bowling, ball-flight information might become more

salient (i.e., less reliance on pre-release information) and could provide opportunities for

increased fidelity of performance when using projection machines. Ball projection

machines, as outlined in section 5.4, are able to replicate the same ball speeds and angle of

release as a ‘live’ performer, providing some level of ‘representativeness’ of practice task

information. It is important to consider the goal of the learning or practice session, as this

may dictate the degree to which a design is a representative simulation of a performance

environment; essentially it is important to sample the important aspects of the

performance context that support these goals. Therefore, the consideration and

assessment of the representative design of ball projection machines nested within

particular performance contexts (e.g., middle wicket practice with typical game demands)

may increase action fidelity at more elite levels. With respect to this idea, it is important to

note that most projection systems available to practice batting in cricket do not currently

support the use of balls with the same properties as those typically used during competitive

performance. This is a major issue since expert performers have been shown to use seam

characteristics of balls to support perceptual decision making in fast ball sports (Hyllegard,

1991). The use of tasks which more closely replicate the flight and bounce characteristics of

a ball used in competitive performance should become a focus for future work.


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5.7. Conclusion

Using projection machines in sport should not be considered dysfunctional. Importantly

they help alleviate workload stresses on bowlers or pitchers during ball delivery which can

lead to overuse injuries in developing and elite performers. Nevertheless, it is disingenuous

to call ball projection machines ‘bowling machines’, because they can only generally

simulate post-ball release information sources during batting practice. They do not allow

learners to pick up specific sources of pre-release information from bowlers’ actions, a vital

part of the information-movement coupling link in batting performance. Current practices

of using such projection technology in athlete development programmes can be enhanced

by using theoretically guided principles to underpin their implementation as a skill

acquisition and performance preparation tool in ball sports. Principles of ecological

dynamics suggest that: (i) their use is likely to differ according to the needs of different skill

groups; (ii) they are most functional when used in high fidelity simulations of performance

environments (e.g., nested in performance settings such as middle wicket practice, or in

combination with video simulations); and (iii) they should supplement practice with ball

projection by real individuals so that all learners can attune to the affordances for action

provided by movements of opponents during ball delivery.

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"We know as much of the history of cricket as we shall ever know now, and we have been

told everything relating to the science of the game. There is no fresh ground to be

explored."

Rev. Holmes (1893)

Chapter 6 – Visual strategies under distinct practice task constraints

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Chapter 6 – Visual strategies of developmental level cricket batters

under distinct practice task constraints

Due to the concerns raised in this thesis with regards to experimental and practice design

utilised in previous research, there was a need to reassess visual strategies of cricket

batters under ball machine and ‘live’ bowler constraints.

This chapter is based on the following article currently being finalised for submission for

peer review:

Pinder, R. A., Mann, D., Renshaw, I., & Davids, K. (to be submitted). Visual strategies of

developmental level cricket batters under distinct practice task constraints.

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6.1. Abstract

Land and McLeod (2000) proposed that cricket batters pursuit tracked the ball for the first

100-150 ms of ball flight following release from a ball projection machine, before making an

early and predictive visual saccade to the anticipated bounce point of the upcoming

delivery; a characteristic more evident in highly skilled batters. However, the use of ball

projection machines in experimental and practice design has recently been questioned and

reviewed (Pinder, Renshaw, et al., 2011). There is a need to discover how differences in the

way a ball is delivered in tasks such as batting against a bowler versus a ball projection

machine, changes the visual search strategies during performance in fast ball sports. This is

a particular concern given the strong reliance on blocked practice using ball projection

machines in developmental training programmes, when a performer is aware in advance of

the predictable, consistent bounce point of the ball. In this Chapter, the performance and

visual search strategies of developmental level cricket batters (n = 5) were assessed when

facing a ‘live’ bowler and a ball projection machine (in both blocked and random ball

delivery conditions). Findings demonstrated that visual strategies of developmental batters

under moderate to high temporal demand (≈ 28 ms·-1) are significantly affected by

differences in pre-release information under changing task constraints. When facing a ‘live’

bowler compared to both ball projection machine tasks, batters initiated the pursuit track

earlier after release, tracked the ball for a longer proportion of early flight and performed

fewer visual saccades. The presence of a visual saccade was not indicative of highly skilled

performance; in fact higher ranked batters performed fewer visual saccades (≈ 60% of

trials) than their lower ranked counterparts (≈ 100%). Furthermore, higher ranked batters

demonstrated an ability to initiate the pursuit track sooner after ball release enabling them

to sample a greater proportion of critical early ball flight. Findings are discussed with

reference to practice routines, providing some evidence to support previous concerns

cautioning against the overuse of ball machines for learning design with developmental

performers (see Chapter 5). Previous interpretations and understandings of visual saccades

and their relationship to visual pursuit tracking appear to have been limited by artificial task

designs, and future research is recommended to advance understanding of perception-

action processes during skilled interceptive actions.


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6.2. Introduction

Spatial-temporal constraints in fast ball sports, such as cricket, can go beyond the intrinsic

limitations in visuo-motor delays and movement times (Regan, 1997; van der Kamp et al.,

2008), and allow for excellent insights into the use of information for the support of action

under changing task constraints (e.g., amount of advanced information provided in

experimental conditions). Analysis of movement models in fast ball sport exemplifies the

functional coupling of perception and action processes, and the synergetic relationship

between a performer and environmental context. Previously, there have been assumptions

that athletes are required to fixate and pursuit track an object for skilled interception

(Regan, 1997), or that high levels of visual function are required for skilled performances to

be sustained. Indeed, many people believed that Sir Donald Bradman, widely regarded as

the greatest cricket batsmen in the history of the sport, benefitted from superior visual

function and reaction times. It is, however, reported that Bradman was discharged from the

army due to poor eyesight (Glazier et al., 2005; Hutchins, 2002) and recent studies by Mann

and colleagues (2010; 2007) demonstrated that no discernible reductions in batting

performances were evident under increasing levels of myopic blur that resulted in

impairment of foveal vision under moderate and high temporal demands (moderate ball

speed in cricket batting: 30-40 m·s-1). It has been surmised, therefore, that skilled

performance in sport is not necessarily dependent on the pickup of accurate trajectory

information of an object to successfully intercept it (Mann et al., 2010). Aligned to this, it

has also been proposed that performers are unable to pursuit track for the entire duration

of a target’s approach due to high ball speeds. For example in cricket batting, it has been

demonstrated that performers used a combination of target pursuit tracking and visual

saccades when intercepting balls delivered from a ball projection machine. Visual saccades

appear to enable a visual ‘catch-up’ of foveal vision in instances where the visual system is

unable to “keep up” with the ball flight (Land & McLeod, 2000). However, to successfully

intercept balls moving at high speeds it is also generally accepted that performers require

the ability to perceive ball trajectory information (e.g., angle of approaching ball, predicted

bounce point) quickly and accurately in order to support shot and movement response

selection. Indeed, information about ball flight elicited from a bowler’s actions has been

shown to contribute towards batters’ judgements of ball delivery type (Müller &

Abernethy, 2006; Müller et al., 2009).

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Smooth visual pursuit tracking strategies during human performance allows for the

extraction of detailed and meaningful information from the environmental context (Spering

& Gegenfurtner, 2008). Tracking objects with foveal vision over longer periods of total flight

time increases the perceptual acuity of the object (e.g., the speed and angle of an

approaching ball to be intercepted). However, Spering and Gegenfurtner (2008) recently

concluded that eye movement strategies, such as the ability to smoothly track objects, are

highly context dependent, with visual strategies constrained by numerous factors, such as

absolute or angular speed of an approaching object, or the predictability of an object’s

flight (McPherson & Vickers, 2004). Land and McLeod (2000) published their seminal and

highly cited paper more than ten years ago; assessing the visual strategies of three

cricketers batting against a ball projection machine. Land and McLeod (2000) assessed the

eye movements of three cricket batters (skilled, experienced and novice) when facing a ball

projection machine under moderate temporal constraints (25 m·s-1). Findings demonstrated

that batters picked up trajectory information after the release of the ball from the machine

for a period of 100-150 ms (equating to 50-80% of total ball flight), before making an

anticipatory saccade to the predicted bounce point. Findings suggested that batters cannot

‘pursuit track’ the ball for the duration of ball-flight, therefore requiring them to pick up

trajectory information as soon as possible to predict bounce point and/or delivery type.

Croft, Button and Dicks (2010) recently attempted to reassess the findings of Land and

McLeod (2000) to establish if there was a critical velocity at which predictive saccades were

required. However, they found that no simple relationship existed between projection

speed and the initial tracking duration. Croft et al. (2010) found that under slow to

moderate temporal constraints (17-25 m·s-1), experienced sub-elite batters used a variety

of highly individual strategies, with considerable variation beyond a group tracking mean of

between 63 and 71% of ball flight. Large within- and between-participant variability

demonstrated that batters used different strategies both before, and immediately after ball

release (e.g., saccade or track); a finding consistent in other fast ball sports (McPherson &

Vickers, 2004; Singer et al., 1998). Some batters in the Croft et al. (2010) study tracked the

ball immediately following ball release and then for the majority of ball flight; a finding

consistent with skilled batters in Land and McLeod’s (2000) study. It is possible that ball

deliveries with longer flight times due to bouncing closer to the batter, and/or moving at

slower velocities, allow for increases in tracking duration and do not exceed the limitations

of the visual tracking processes. These findings suggest the ability of a batter to pick up ball

flight information as early as possible may afford a longer tracking duration. Previous

interpretations suggest that the occurrence of a visual saccade may be due to a critical


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change in vertical velocity at ball release (e.g., short balls that bounce further away from

the batter and are delivered on a steeper angle from release) (Land & McLeod, 2000).

Latencies between the release and initial pursuit tracking of the ball in both instances may

account for the appearance of predictive saccades, with some skilled batters in Croft et al.’s

(2010) study able to track directly from release and therefore may in fact be able to counter

this need to ‘catch up’ with the ball.

A concern, however, has been recently highlighted, with the role of ball projection

machines in performance and athlete preparation being questioned and reviewed (for a

comprehensive review see Pinder, Renshaw, et al., 2011; also see Chapter 5). There is a

need to discover how differences in the way a ball is delivered in tasks such as batting

against a bowler versus a ball projection machine changes the visual search strategies

during performance in fast ball sport. This is a particular concern given the widespread

acceptance of the findings of the Land and McLeod study (based on 3 performers of widely

varying skill level). Additionally, the issue is important on a practical level given the

tendency for developmental programmes in cricket to utilise projection machines to

provide large volumes of blocked practice (e.g., via practice where a performer is aware in

advance of the predictable, consistent bounce point of the ball; Woolmer et al., 2008).

Research comparing batting performance against ball machines and ‘live’ bowlers has

demonstrated significant differences in spatio-temporal characteristics of batting

performance and movement responses (Mann et al., 2010; Pinder, Davids, et al., 2011a;

Pinder et al., 2009; Renshaw et al., 2007). These differences are a result of the fact that

batting against a ball machine removes the critical information sources present in a

performance context representative of facing an opponent (e.g., removal of bowler’s

movement information such as angle of arm at ball release). Failure to be able to attune to

this crucial information source leads to a critical delay in movement initiations of

developmental level batters. This is because early ball flight needs to be sampled before the

bounce point can be identified to enable the batter to make a decision to move forward or

backward to intercept the ball1. It is this increased temporal demand that ultimately results

in a reduction in batting performance.

1 Balls that pitch short, or further away from the batter will bounce higher and the batter needs to step back to typically intercept the ball at approximately waist-chest height. In contrast, balls that bounce close to the batter can be stepped forward to, and be intercepted around knee height.

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Additionally, some researchers have utilised video projections to provide experimental

control between participants (e.g., Barras, 1990). Barras (1990) suggested that batters

should focus on the ball in the bowler’s hand up until less than 1 second before the release

(during the bowlers final delivery stride), at which point they should move their visual gaze

to the anticipated release point. However, due to the separation of the perception and

action processes in task designs (removal of a representative response), the results of such

studies are questionable (see section 2.8; also see Chapter 4). For example, Dicks and

colleagues (2010) recently observed different visual strategies present in soccer

goalkeepers under different degrees of perception-action separation. Croft et al. (2010)

reported that batters used very different visual strategies before the release of the ball,

with some batters looking directly at the ball machine outlet, while others ‘parked’ their

gaze on an anticipated trajectory of flight. Similar to previous spatio-temporal analyses of

batting performance, it appears that experience with a ball projection machine may lead

batters to tend towards a predictive visual strategy (see Chapter 5; also see Renshaw et al.,

2007), which may not be indicative of other performance settings; based on this body of

work, it is intuitive to suggest that differences are likely to exist in visual strategies under

changing task constraints in cricket batting. Intuitively, the removal of information from the

bowler’s action may have led to the adoption of specific visual strategies at, and

immediately after, ball release in previous studies (e.g., Croft et al., 2010; Land & McLeod,

2000) However, until now few attempts have been made to assess visual strategies in

cricket batting, and to our knowledge none that have compared visual strategies under ball

machine constraints to those representative of a performance context of facing a ‘live’

opponent.

The previous discussion raises two important issues: i) no previous work has reported the

frequency at which saccades occur during performance under varying task constraints, and

ii), analyses have only been completed with performers facing ball projection machine task

constraints under moderate time constraints for highly skilled or experienced performers

(with the exception of one novice participant – see Land & McLeod, 2000) . The use of

projection machines may increase the latency between release and initial pursuit tracking

initiation. Indeed large volumes of blocked practice experience using a ball machine may

increase the predictability of the ball trajectory and result in visual search strategies not in

line with those adopted when the bounce point is not known in advance. Understanding of

the functional role of visual saccades in fast ball sports (and their relationship to the initial

pursuit tracking strategy) may, therefore, currently be at best limited, or at worse


109

misleading given previous assessments under artificial task constraints such as batting

against ball projection machines rather than real bowlers. An interesting question concerns

whether visual strategies may be compromised under ball projection machine performance

conditions. Previous research has suggested that an important element of expertise in

cricket batting against a ball projection machine is the ability to initially pursuit track early

in ball flight before accurately making early visual saccades to a predicted landing point of

the ball; these are critical aspects since these pursuits or saccades may differ substantially

between ball machine and ‘live’ bowler task constraints.

The aims of the study reported in this Chapter were to assess the pursuit tracking and

saccadic strategies of developmental performers in cricket batting under moderate to high

temporal demand when presented with three distinct tasks. Based on previous work and

developmental practices, batters were required to face ‘live’ opponents bowling a ball, a

ball projection machine delivering balls in a random order (where a coach follows a random

script for targeted ball bounce location and therefore changes in the angle of the ball

machine head), and a ball machine delivering balls in a blocked order (where balls at three

distinct ball-length/ bounce points were presented in blocked order with little between trial

variation in machine positioning). It was hypothesised that developmental batters would

pursuit track sooner after ball release when facing a ‘live’ bowler compared with ball

machine task constraints, enabling earlier and more accurate saccadic predictions.

Furthermore, it was predicted that higher skilled developmental batters would also show

distinct differences in visual strategies than their less skilled counterparts. Specifically,

based on previous research it was predicted that higher skilled batters would make early

predictive saccades to the expected bounce point.

6.3. Method

Participants

Six junior cricketers (age 16.32 ± 0.30 years; 8.83 ± 1.72 years of competitive cricket

experience) were recruited for the study. Participants were matched in height (1.76 ± 0.04

m) to standardise body-scaling of ball-bounce performance regions (see Figure 6.1), and

were considered to be moderately skilled junior performers at the control stage of motor

learning by 2 Cricket Australia Level 3 coaches and motor learning specialists (Newell,

1985). Each batter faced three bowlers during performance (n = 5; mean age: 15.25 ± 0.99

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years) due to work load concerns on junior bowlers (Dennis et al., 2005). Bowlers had

similar conventional bowling (ball delivery) actions and physical attributes (all right arm

bowlers; peak height of bowling arm: 2.10 ± 0.05 m; bowling speed: 28.29 ± 0.96 m·s-1).

Peak height was measured from a sagittal view of the bowling line. Bowling workloads were

controlled by an experienced Australian Level 3 cricket coach. Bowling speed was assessed

prior to data collection, and monitored throughout the testing session using a sports radar

gun (Stalker Radar, Texas). One batter was later removed from the analysis due to

equipment failure. All participants wore full protective equipment and provided informed

consent to a protocol approved by a university ethics committee.

Table 6.1. Participant information. CPE= Competitive playing experience in years; BPW = Self-report

average of ‘balls’ per week practiced using a ball projection machine; QoC = Quality of contact; FoBS

=Forcefulness of bat swing.

Batter CPE Ball Machine BPW Within task

QoC ranking

Within task

FoBS ranking

Coaches

Ranking

Combined

Skill Ranking

1 11 100-200 1 1 2 1

2 9 30 2 3 1 2

3 8 20 3 2 4 3

4 6 0 4 4 3 4

5 9 100 5 5 5 5

Procedure

Performance observations occurred in the participants’ regular practice facility. Batters

undertook three distinct experimental tasks - batting against: i) ‘live’ bowlers, ii) a ball

machine ‘random’, and iii) ball machine ‘blocked’ projection regimes. In the blocked

condition, the batter was aware of the intended bounce point of the ball delivered from a

ball machine, and three different areas for the bounce point (ball-length) were presented in

blocked conditions until required trials were completed. In the random condition, the three

different bounce points were randomised by the experimenter and coach operating the

machine. Task conditions were counterbalanced between participants to control for order

and learning effects. Batters were appropriately matched to the skill level of the bowlers.

Due to the large between-participant variability seen in previous work (e.g., Croft et al.,

2010; Land & McLeod, 2000), batters were ranked by their coach, and rankings were

supported by within-task measures of quality and aggressiveness of their batting


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performance (see Table 1; also see Figure 2). Batters 1 and 2 are considered to be top order

batsmen (highly skilled relative to participant group – state representative level), batters 3

and 4 were middle order batsmen (moderately skilled relative to group) and batter 5 was a

low order player (low skilled relative to other batters)2. Given potential impact of

experience of facing ball machines on eye tracking and movement responses, it was

important to consider information regarding individual practices. All batters had experience

of playing against the same ball machine used in the study; however individual batters

reported different weekly volumes of practice under ball machine constraints (i.e., number

of balls per week - see Table 6.1).

Prior to data collection, three distinct spatial areas (ball-lengths) for ball bounce were

chosen based on consultation with the coach. These areas (see Figure 6.1) were body-

scaled to the batters in the study, and were based on typical ball-lengths focused on during

batting skill development to provide a representative sample of deliveries a batter might

face in a match situation (Woolmer et al., 2008); i) a ‘Full-length’ ball that bounces close to

the batter (2.5-3.5 m from the stumps) and is typically intercepted at shin height, ii) a

‘Good-length’ ball (5-6 m) bouncing to the height of the top of the stumps (bowlers’ target

in cricket) typically intercepted at approximately knee height, and iii) a ‘short-length’ ball

(8-9 m) which bounces higher, and typically requires a batter to move backwards to

intercept the ball at around waist to chest height. The inclusion of deliveries which required

batters to move forward and back ensured that batters had a crucial decision to make on

each trial; batters were not primed to move in one direction which might have influenced

visual measures.

The same balls (‘Oz’ ball machine ball) were used across all conditions to provide

consistency in bounce and flight characteristics. The ball machine (Jugs Inc., Tualatin,

Oregon) was set at the same height and bowling speed recorded from the bowlers to

replicate their ball delivery characteristics (e.g., release speed, angle of delivery). Bowlers

followed an individual and randomised script of pitching locations to target, and waited for

a ready signal from the batter before beginning their approaches. The randomised scripts

were replicated in the ball machine condition; where between trials, batters were

instructed to turn and walk to touch the back of the protective net behind the stumps 2 Top order players are those in the early positions (1-5) of a cricket batting line-up, and are typically the best batters. Middle order players (positions 6-8) are typically ‘all rounders’, who both bat and bowl. Lower order batters are typically the bowlers who have the lowest batting skill (positions 9-11).

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allowing the angle of the machine head to be altered. In addition to batters being blind to

any initial adjustment of the machine head, the ball machine operator was able to make

subtle changes to the trajectory at release that could not be detected by the batters. The

ball machine was operated by a highly experienced Australian Level 3 coach using a

standardised pre-delivery routine used in practice; the operator waited for a ready signal

before holding up the ball for the batter to see before lowering directly into the machine

(see Pinder, Davids, et al., 2011a; Renshaw et al., 2007; Shim et al., 2005). The time

between the ball entering and exiting the machine (approximately 1 s) was consistent

across all conditions and ball release trajectories. Similar to previous work (Pinder, Davids,

et al., 2011a; Shim et al., 2005), the sound of the machine was expected to provide

supportive information for the prediction of release through previous ball machine

experience (i.e. perceptual attunement of batters’ responses).

Batters were instructed to perform as they would in a competitive performance context, by

attempting to score as many runs as they could while avoiding being bowled (ball hitting

stumps). No specific task instructions or knowledge of the experimental aims were

provided. Batters were given six practice trials before the commencement of each

condition. Participants continued to bat until they had completed a minimum of five trials

at each ball-length (see Figure 6.1). Participants generally faced 20-36 deliveries in each of

the interceptive conditions (ball machine and bowler) to generate the required number of

shots for data analysis, in line with previous empirical research (Stretch et al., 1998). A

trained research assistant noted the location of ball-bounce ‘live’, and bounce location was

confirmed post hoc using video footage (see below). Trials in which the ball did not bounce

within specified locations were excluded from the analysis.


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Figure 6.1. Side and above views of experimental set-up

Data collection

Participants wore a mobile eye-tracking unit under a customised batting helmet (25 Hz:

Mobile Eye, Applied Sciences Laboratories) to track the location of visual gaze during

batting performances (see Figure 6.2). The Mobile Eye unit was attached to a Digital Video

recording device (Sony DV Walkman) worn in a lightweight pouch around the lower back

during the batting tasks. The unit (≈ 1 kg) was fitted securely so it did not obstruct the

batters movement requirements. The DV unit was attached to a Radio Frequency (RF)

transmitter allowing the eye movement footage to be sent wirelessly to a receiver (large

LCD display) for real time monitoring by an experienced researcher. Consequently, any

changes to the location of the scene or eye cameras were able to be detected, maximising

the percentage of useable trials for data analysis; a major concern in previous work. The

customised helmet had a portion of the peak removed to minimise obstructions or ‘knocks’

to the Mobile Eye unit. Calibration of the visual gaze footage was performed using a

number of pre-determined locations within the batters expected visual scene (for example

marked distances on the ground and mouth of the ball machine or ball at a typical release

position of a bowler). Re-calibrations were performed before and after each condition,

anytime the unit was moved, or when a change in the scene or eye cameras was detected.

These checks allowed for the successful analysis of 95% of all collected footage (including

trials not selected for analysis).



BatterFull Good Short

Bowler/ Ball Machine

Stumps3.5 m

6 m9 m

Ball Release

0.71 m

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A series of video cameras were used to capture the behavioural responses of the batters,

and link to the eye movement recordings. Two event-synchronised video cameras (Casio

EXILIM Pro EX-F1: 60 Hz) captured participants’ movement organisation and batting

performance (anterior view), and moment of ball release (perpendicular to delivery line)

concurrently. A third camera (Sony HVR-V1P, 50 Hz) was positioned behind the batter and

allowed the synchronisation of eye-movement footage with the moment of release,

bounce-point and batters behaviour. All footage was analysed frame-by-frame and visual

and behavioural responses were coded with respect to key events (e.g., release, ball

bounce, bat-ball contact).

Figure 6.2 – A participant wearing full protective equipment and mobile eye-tracking unit

Dependent variables

Performance scores

Batting performance was assessed using validated measures of Quality of Contact (QoC; see

Müller & Abernethy, 2008), and Forcefulness of Bat-swing (FoBS; see Mann et al., 2010).

QoC indicates the quality of the interception as 2, 1 or 0 for good, poor and no bat-ball

contact, respectively. FoBS indicates the aggressive intent of the action, and an indication

of the likelihood that runs would have been scored (i.e. a higher score represents a more


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difficult shot requiring a greater degree of spatial-temporal precision); scores of 2, 1 and 0

were used for high, moderate and low forcefulness, respectively. Reliability was assessed

on a selection of 20 random trials (≈10% of all trials). Intra-rater reliability was assessed by

comparing two video reviews (with a 4-week break) of the first observer, while inter-rater

reliability was assessed by comparing the scores of the first observer with those of a second

observer. Strong correlations were found for both intra- (rs = .87) and inter-rater (rs = .91)

reliability, consistent with previous work (Mann et al., 2010).

Visual tracking

Batters’ visual behaviours were subjected to frame-by-frame analysis from ball release to

bat-ball contact. Batters were considered to be ‘tracking’ the ball when the gaze-ball

discrepancy was less than 1.5° in accordance with previous work (Croft et al., 2010). A

saccade was coded when the gaze was seen to transition between two distinct locations on

the scene view in line with previous work (Land & McLeod, 2000). Four measures of visual

responses were analysed: i) pursuit tracking initiation (PTI) was coded as the first frame of

the smooth pursuit track following ball-release (within 1.5°), ii) pursuit tracking duration

(PTD) was defined as the initial and uninterrupted visual tracking duration following PTI, iii)

frequency/ number of visual saccades performed, and iv), timing of a saccade (if present).

All values are reported as a percentage of ball-flight from release to bounce point to allow

for comparison with previous work. Visual tracking and saccade variables were

independently assessed by two trained researchers. A random selection of trials (n = 20)

was used for inter- (Interclass Correlation Coefficient = .86) and intra-rater reliability (.88)

checks. Furthermore the presence and timing of saccade values revealed inter-rater

reliability scores of .96.

Data Analysis

Mixed model ANOVAs were used on performance scores and visual tracking variables;

allowing for the modelling of dependent variables as within-participant factors between

experimental constraints (e.g., batting tasks). Between-participants tests were used to

allow for comparisons across dependent variables on an individual level, with data checked

using Levene’s test of equality of error variances. Given recent arguments in behavioural

sciences that the tendency to average performance data for statistical analysis can mask

functional variability observed in individual participants (see Dicks, Davids, & Button, 2010;

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Schöllhorn et al., 2009), results were assessed on a group and individual basis. This is

particularly important given findings in visual search data of high between- and within-

individual variability (Croft et al., 2010; Land & McLeod, 2000; Singer et al., 1998). In

instances where data violated the sphericity assumption, a Greenhouse–Geisser correction

adjusted the degrees of freedom for treatment and error terms of the repeated measures

variables. Post hoc pairwise comparisons were undertaken to assess which comparisons

were statistically significant in each instance. Bonferroni corrections, with adjustments to

an alpha level of .01 were used to control for type I error and account for possible

interdependence between variables and multiple comparisons (Field, 2009). Finally, partial

eta-squared (ηp2) values were provided for each ANOVA to provide an indication of the

effect size or magnitude of the differences in variability. Due to the nature and current

unpredictability of the occurrence of visual saccades, linear mixed models were used to

analyse timing of visual saccades. Linear mixed models allow for individual differences in

addition to group means, but also accommodate multiple missing data points (i.e. analysis

of trials in which a visual saccade was present was not affected by trials without a saccade)

(Krueger & Tian, 2004). Bonferroni corrections, with adjustments to an alpha level of .01

were used to control for type I error and account for multiple comparisons (Field, 2009).

Finally, Pearson correlations were used to assess key relationships between visual tracking

measures and batter skill level (e.g., PTD versus skill level).

6.4. Results

Batting performance scores

A mixed model ANOVA revealed significant effects for QoC across experimental (batting)

task constraints, F(2,140) = 6.35, p < .01, η2 = .22, and individual batters, F(4,70) = 4.203, p <

.01, η2 = .19, but not a significant interaction between batter and experimental condition,

F(8,140) = 1.82, p > .05, η2 = .09. Bonferroni post hoc comparisons with an adjusted alpha

level of .01 on QoC revealed that batters 1 and 2 scored significantly higher in interceptive

quality than Batter 5. Group means demonstrated that there was a significant reduction in

QoC when facing a randomised ball machine, compared to both blocked and ‘live’ bowler

conditions (p < .01). Individual results between experimental conditions are presented in

Figure 6.3; two batters actually maintained or increased the number of good contacts when

playing against the ball machine when compared to a ‘live’ bowler (batters 1 & 5). Although

batter 5’s scores were still significantly lower, scores under blocked machine task


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constraints were similar to other batters. Furthermore, a mixed model ANOVA revealed a

significant main effect for FoBS on experimental task F(2,140) = 10.66, p < .01, η2 = .13.

There was no significant effect for batter, F(4,70) = 1.69, p > .05, η2 = .09, nor was there an

interaction between batter and experimental task, F(8,140) = 1.32, p > .05, η2 = .07. All

batters were similarly affected by the experimental constraints, where there were

significant reductions in FoBS scores in both blocked (p < .01) and random machine

conditions (p < .05), compared to facing a ‘live’ bowler.

Figure 6.3. Individual (a & b) and group (c) performance scores under changing task constraints.

Pursuit tracking

A mixed ANOVA revealed significant main effects for PTI on experimental task, F(2,140) =

26.66, p < .01, η2 = .29, and batter, F(4,70) = 4.237, p < .01, η2 = .20, with a significant

condition x batter interaction, F(8,140) = 3.27, p < .01, η2 = .18. Bonferroni post hoc

comparisons with an adjusted alpha level of .01 on PTI revealed that batters initiated the

pursuit track of the ball significantly earlier after release when facing a ‘live’ bowler (after

24.86 ± 12.65% of the total ball-flight from release to bounce; i.e. ≈25% of the ball-flight

had already been completed) in comparison to both blocked (36.80 ± 16.01%) and random

0.000.200.400.600.801.001.201.401.601.802.00

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ball machine constraints (33.96 ± 14.44%). Large standard deviations are indicative of

differences between individual batters. Batter 1 (22.25 ± 8.11%) initiated pursuit tracking

significantly earlier in ball flight than Batters 3 (33.55 ± 9.56%), 4 (34.38 ± 4.10) and 5 (39.03

± 7.55%). Figure 6.4 shows both group and individual differences in PTI times across

experimental task constraints. Furthermore, a mixed model ANOVA revealed significant

main effects for PTD on experimental task, F(2,140) = 13.45, p < .01, η2 = .16, and batter,

F(4,70) = 14.56, p < .01, η2 = .45, and an insignificant task x batter interaction, F(8,140) =

.95, p > .05, η2 = .05. Bonferroni post hoc comparisons with an adjusted alpha level of .01

on PTD revealed that batters pursuit tracked the ball for a significantly longer period of ball

flight following PTI when facing a ‘live’ bowler (51.07 ± 13.36% of the total ball-flight from

release to bounce point) in comparison to a both blocked (45.78 ± 16.78) and random ball

machine tasks (40.30 ± 15.21%). Additionally, PTD was significantly longer under blocked

compared to random practice conditions. Again, large standard deviations reflect that there

is a difference between batters. Batter 1 (63.17 ± 8.71%) pursuit tracked the ball for a

greater percentage of ball flight than all other batters, with Batter 2 (48.15 ± 12.16%) also

tracking for longer than Batter 5 (36.01 ± 7.76%). Figure 6.4 provides both group and

individual PTDs across experimental task constraints presented as a percentage of release-

bounce point to allow for comparison with previous work (see Croft et al., 2010; Land &

McLeod, 2000). Pearson Product Moment correlations demonstrated that there were

highly significant relationships between the timing of the PTI and the total PTD for both

bowler (r = -.97, p < .01) and random machine tasks (r = -.93, p < .05), but not for the

blocked machine condition (r = -.65, p = .23). Initiating a pursuit track earlier allowed for a

greater overall time spent pursuit tracking the ball (PTD), rather than an earlier visual

saccade as would have predicted from previous research (e.g., Land & McLeod, 2000).


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Figure 6.4. Individual and group pursuit tracking responses under changing task constraints; a) PTI; b)

PTD; c) group means. For 6.4a and 6.4b lines indicate individual batters means across all conditions.

Visual saccades

A mixed model ANOVA revealed significant main effects for number of saccades on

experimental task, F(2,140) = 4.99, p < .01, η2 = .07, and batter, F(4,70) = 6.90, p < .01, η2 =

.28, with an insignificant condition x batter interaction, F(8,140) = .82, p > .05, η2 = .05.

Bonferroni post hoc comparisons with an adjusted alpha level of .01 on number of saccades

revealed that batters used a visual strategy which incorporated a visual saccade in

significantly fewer trials when facing a ‘live’ bowler (72.33%) when compared to both

blocked (85.33%) and random ball machine tasks (88.00%). Additionally, comparisons

demonstrated that Batter 5 (97.87%) completed a significantly larger proportion of

saccades across all tasks, when compared with both Batter 1 (68.89%) and Batter 2

(66.67%). Both group and individual responses are presented in Figure 6.5. Broken down by

length, batters completed more visual saccades when balls were ‘short’ (B: 81% of trials;

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BMB: 100%; BMR: 100%) compared to ‘good’ (B: 60%; BMB: 82%; BMR: 92%) and ‘full’ (B:

69%; BMB: 76%; BMR: 72%).

When saccades were present in a batter’s visual search strategy, a mixed model ANOVA

revealed that there were significant main effects for the timing of the saccade (as a % of

ball flight) on both experimental task, F(2,179) = 7.97, p < .01, η2 = .12, and batter, F(4,177)

= 3.51, p < .01, η2 = .09. Post hoc comparisons revealed that when present, saccades

occurred later in the flight of the ball (e.g., closer to ball bounce location) when facing a

‘live’ bowler (90.47 ± 9.43%), compared to both blocked (84.18 ± 13.08%) and random ball

machine conditions (80.63 ± 16.23%). Additionally, comparisons revealed that Batter 1

(90.99 ± 7.34%) produced visual saccades significantly later in the ball flight than Batters 3

(82.19 ± 9.78%) and 5 (81.23 ± 6.33%). Figure 6.6 provides an analysis of group data for

trials including a visual saccade. Under ‘live’ bowler conditions the pursuit track is initiated

earlier, and the batters gaze is allowed to fall behind the ball before performing a later

saccade closer to the bounce point of the ball (i.e. 100% ball flight). Conversely, under ball

machine conditions the pursuit track is initiated later, with less time spent with their visual

gaze behind the ball before performing a visual saccade.

Further t-tests revealed that PTD was significantly shorter when a saccade was present in a

batter’s visual strategy, compared to when a saccade was not required, consistent across

‘live’ bowler, t(73) -1.99, p < .05, blocked, t(73) -3.68, p < .01, and random task constraints,

t(73) -3.90, p < .01.


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Figure 6.5. Individual and group visual saccade responses under changing task constraints; a)

Number of saccades (as a % of total trials); b) Timing of visual saccade (as % of release-bounce

point); c) group means. Lines (a and b) indicate individual batters means across all conditions.

Figure 6.6. Group means for the relationship between visual pursuit tracking and occurrences of

saccades. PTI = Pursuit track initiation; PT-end = the offset of the pursuit track duration. Bars

represent group means across all three experimental tasks.

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Individual responses and skill level

Figures 6.7 and Table 6.2 provide a summary of visual tracking variables and skill ranking for

individual level analysis. Skill ranking correlations revealed some significant relationships

between a batter’s ranking and visual tracking variables (see Table 6.2). Correlations are

less evident in findings against a ball projection machine, compared to when batting against

a ‘live’ bowler. Results demonstrate a significant relationship between skill level (based on

QoC, FoBS and coach ranking) and tracking initiation and total duration, in addition to total

number of saccades. High ranked batters begin the pursuit track earlier than middle and

lower ranked batters, and track for a longer proportion of ball flight; a finding particularly

evident when facing bowlers (see Figure 6.5a and 6.5b).

Figure 6.7. Individual batter mean percentage scores across all conditions for visual tracking

variables. Batters are ordered by skill level (highest to lowest, left to right). PTI = Pursuit track

initiation; PTD = pursuit track duration.

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Table 6.2. Correlations of batters skill ranking with visual tracking variables.

All shots Bowler Ball machine

Blocked

Ball machine

random

r p r p r p r P

PTI .95 .01* .94 .04* .67 .22 .87 .06

PTD -.90 .03* -.91 .03* -.88 .06 -.84 .07

Timing of saccade -.67 .22 -.61 .27 -.60 .28 -.71 .17

Number of saccades .91 .02* .75 .15 .94 .02* .87 .06

6.5. Discussion

Land and McLeod (2000) proposed that a key characteristic of skilled batting performance

was the early and accurate visual saccade to the anticipated bounce point of the ball

following a short period of pursuit tracking. However, one major concern was that these

pursuit track characteristics were observed under experimental constraints representative

of an artificial training task; batting against a ball projection machine. The data in this

Chapter demonstrated that significant differences exist between the visual characteristics

of developmental batters under changing task constraints, including a representative task

of facing a ‘live’ opponent delivering a ball.

Performance and visual strategies

Similar to previous work, batting performance scores (QoC/ FoBS) were significantly

reduced when responding to balls delivered from a projection machine (see Figure 2; also

see Chapter 3). All batters (except batter 5) had a greater or equal performance (QoC)

when facing a bowler compared with a ball machine; additionally all batters performed

better under blocked constraints compared with a random ball machine condition. It is

apparent that pre-knowledge of the upcoming delivery allows the batter to greatly increase

the interceptive quality of the resulting action, however, it should be noted that all batters

had a reduction in FoBS (an indication of the aggressive intent of the shot) in the blocked

condition. Contrary to prediction, batters reduced the forcefulness of the hitting action

when they had pre-knowledge of the upcoming delivery. It may be that batters premeditate

the required action, resulting in lower levels of adaptive decision making behaviour in these

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well practiced ‘short’, ‘good’, and ‘full’ areas, with fewer different shots and deepening of

performance ‘attractor’ states (see Chapter 7; also see Pinder, Davids & Renshaw, in press).

As hypothesised, and in accordance with performance scores, when batters were provided

with advanced information of a bowler’s action (beyond ball-flight from release provided by

a machine), they were able to significantly reduce the delay between release and the

initiation of a smooth pursuit track of the ball in flight (see Figure 6.4). Consequently,

batters were all able to pursuit track the ball for a greater percentage of the ball-flight

when facing a ‘live’ opponent (40-70% ball-flight), compared to both blocked and random

conditions (30-65%; note the large within-participant variability). Collectively,

developmental batters visual tracking performance was similar to that seen in previous

work (Croft et al., 2010; Land & McLeod, 2000); with few discernable differences

demonstrated for PTI between blocked and random ball machine conditions (however see

individual differences below; also see Figure 6.4). However, PTD was longer under blocked

conditions compared to random; a suggestion that some pre-knowledge of upcoming

delivery was useful in aiding the visual strategy, and accordingly QoC for all batters (see

Figure 6.2). It may be that despite any discernible difference in initiation times, pre-

knowledge of the possible angle of delivery allowed batters to ‘wait’ for the ball and track

for a longer duration once the correct angle was confirmed; this appears to be particularly

evident for Batter 1 (see below).

Batters facing a ball machine tracked the ball in a similar manner to batters in the study of

Land and McLeod (2000), however, when facing a ‘live’ opponent bowling the ball, batters

initiated smooth pursuit tracking significantly earlier (≈ 25% of the ball-flight), continued it

for significantly longer, and therefore sampled a greater percentage of the critical post-

release ball flight information observed to define skilled performance in cricket batting (see

Müller et al., 2009). It was hypothesised that earlier initial pursuit tracking behaviour would

result in earlier saccades to a predicted bounce location (e.g., a quicker recognition of ball

length). However, earlier PTIs resulted in significantly longer PTDs for all batters when

facing a bowler, removing the need for earlier predictive saccades. In fact, all batters

significantly reduced the number of visual saccades they performed against bowlers,

compared to batting against the ball machine (for an exception see Batter 1, Figure 6.5; also

see below). Furthermore, when these saccades were present (i.e., when they were required

as part of the batters visual strategy) they occurred significantly later in ball-flight against

bowlers (> 90% of the ball-flight), suggesting that batters produced more accurate saccades


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at the critical timing of bounce point. Taken together (see Figure 6.6), these visual

measures suggested that when facing a bowler, batters pursuit tracked for a longer period

of the early ball flight before ‘falling behind’3 the ball. At this point batters appear to make

no instant visual saccade but proceed to follow ‘behind’ the ball before making an accurate

visual saccade to the bounce point. In trials where no visual saccade was evident, batters

tracked the ball for a greater proportion of ball flight before falling behind, again making no

attempt to catch up via foveal vision; this suggests that the required information may have

been extracted over this longer tracking duration, or enough information was gained to rely

on peripheral vision. Under ball machine task constraints, developmental performers

demonstrated visual search strategies in line with previous research (Croft et al., 2010; Land

& McLeod, 2000). Batters tracked the ball for a similar length and period of ball flight,

before making an early saccade to the anticipated bounce point following a short lag

behind the ball. It is possible that these key differences between task constraints

demonstrate that batters adopted both a predictive strategy (when facing a bowler) and a

reactive strategy (when facing a ball machine), when functional. Batters picked up ball-

flight information later, seemingly allowing the ball to ‘wash over the retina’ therefore

appearing to track for a shorter period of time, before making a reactive and necessary

saccade ahead to an anticipated bounce point (Glazier, Davids, & Bartlett, 2002).

Individual and skill related differences

As discussed previously, batters tended to perform better on all performance and visual

measures when facing a bowler, compared with either of the ball machine tasks.

Interestingly, two Batters (the best and worst) maintained or increased the quality of action

(QoC) when facing blocked trials against a ball machine when compared to a ‘live’ bowler

(see Figure 6.2); both of these Batters (1 & 5) reported large volumes of weekly practice

time dedicated to this specific task. Furthermore, Batter 1 initiated the pursuit track

significantly later against the blocked machine with a significant reduction in the number of

visual saccades required without detriment to performance. Small individual differences

between ball machine tasks may be indicative of differences in practice histories or skill

level with the specific type of machine used, however, similarities between the two distinct

delivery methods demonstrate that the differences between visual and performance

3 A phrase used to demonstrate an instance when the foveal vision does not keep up with the previous pursuit track, lagging behind the ball falling below the visual gaze. Generally the performer still appears to be making continual adjustments following the line of the ball.

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measures are a result of the removal of task specific information sources (e.g., a bowler’s

action) rather than differences in the additional information (e.g., knowledge of likely

bounce point). Despite being highly skilled under all conditions, distinct visual strategies of

Batter 1 may be an indication that a performer has learned to ‘bat against the machine’

(Pinder et al., 2009). Although self-reported scores do not provide a detailed history of use,

they do allow us to assess the current and shorter term volume of practice under machine

conditions. Interestingly, the three Batters (2, 3, & 4) who reported little weekly ball

machine use demonstrated larger differences between the bowler and machine task

constraints, and few discernible differences between blocked and random conditions.

QoC and FoBS scores were used as within-task assessments of skill level to support a

coaching assessment and provide an overall ranking; allowing us to assess any visual

differences within the current participant group. Furthermore, as ranking is partly based on

overall experimental task performance, some inferences can be made regarding the link

between task and visual performance. Figure 6.7 demonstrates the four key measures and

their relationship to the batters rankings. Although assessments in the current study are

only based on 5 batters there are some significant differences between (relatively) high and

low skilled batters. Top order Batters (1&2) outperformed their lower skilled counterparts

(middle order 3 & 4 and lower order Batter 5) on all visual measures. Higher skilled batters

initiated the pursuit track of the ball earlier following release, allowing for a greater PTD,

and therefore greater sampling of early ball-flight. These findings are particularly evident

when facing a ‘live’ opponent (see Table 6.2). Results also demonstrated that the presence

of a visual saccade is not necessarily required for successful performance; indeed the

highest skilled Batter (1) within the current study performed the least number of saccades,

while the lowest skilled Batter (5) performed the most (in almost every trial; number of

saccades performed appears highly related to skill level of these developmental batters –

see Figure 6.7). It may be that visual training batters to pick ball up earlier from the

moment of release may decrease the number and presence of visual saccades, in the first

instance. However, it may be that as players progress through the developmental pathways

that require them to face bowling of higher speeds, earlier tracking allows faster prediction

of bounce point under greater temporal demand. It could be speculatively suggested that

the top order players had developed their ability to initiate pursuit tracking earlier as a

result of being exposed to faster bowlers for greater periods of time and as a consequence

of performing in adult competitions alongside their commitments with the school team.

This potentially crucial idea clearly requires further empirical testing.


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6.6. Conclusion

Both group and individual interpretations of the data outlined above suggest that

significant and critical differences may exist between visual search strategies when facing

bowlers and ball machines. Based on findings of the current study, it is therefore suggested

that large volumes of practice under artificial task constraints (see Chapter 5) may have

influenced the interpretations made in previous research. Findings suggest that

understanding of the specific role of visual saccades and their relationship to pursuit

tracking strategies in fast ball sports are currently limited. Here, batters were, over multiple

trials, able to track the ball for an adequate period of ball-flight to negate the use of visual

saccades to ‘catch-up’ with the ball even under greater temporal demand than seen in

previous research. It could be argued that for an expert batter the moderate temporal

demand utilised in previous studies (e.g., ball machine at 25 m·s-1) would not represent a

difficult task, and they may have accrued a large history of practice against such task

constraints heavily influencing previous interpretations (Croft et al., 2010; Land & McLeod,

2000). Further work is needed to assess the visual strategies of highly skilled performers

under similar task constraints studied here, with work focussed on integrating visual search

studies with kinematic information to understand the perception-action process in rich

performance environments (e.g., Panchuk & Vickers, 2006). Future work should continue to

assess performance under both bowler and machine task constraints to further our

understanding of the specific role of visual saccades in skilled performance in fast ball

sports, and ensure that research and practice tasks are representative in their learning

design (see Chapter 4 & 5).

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“Act always so as to increase the number of choices.”

H. v. Foerster (1911-2002)

Chapter 7 – Meta-stability in dynamic interceptive actions

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Chapter 7 – Meta-stability and emergent performance of dynamic

multi-articular interceptive actions

The following chapter provides evidence for the differences in movement organisation

under changing task constraints. The chapter is a product of the emergent nature of both

the programme of research, and movement organisation under representative practice

conditions. The chapter demonstrates how meta-stability is an important concept for

learning design in sport.

This chapter is based on the following peer-reviewed article:

Pinder, R. A., Davids, K., & Renshaw, I. (2012). Meta-stability and emergent performance of

dynamic multi-articular interceptive actions. Journal of Science and Medicine in Sport.

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7.1. Abstract

Adaptive patterning of human movement is context specific and dependent on interacting

constraints of the performer-environment relationship. Flexibility of skilled behaviour is

predicated on the capacity of performers to move between different states of movement

organization to satisfy dynamic task constraints, previously demonstrated in studies of

visual perception, bimanual coordination, and an interceptive combat task. Meta-stability is

a movement system property that helps performers to remain in a state of relative

coordination with their performance environments, poised between multiple co-existing

states (stable and distinct movement patterns or responses). The aim of this study was to

examine whether meta-stability could be exploited in externally-paced interceptive actions

in fast ball sports, such as cricket. Here we report data on meta-stability in performance of

multi-articular hitting actions by skilled junior cricket batters (n = 5). Participants’ batting

actions (key movement timings and performance outcomes) were analysed in four distinct

performance regions varied by ball pitching (bounce) location. Results demonstrated that,

at a pre-determined distance to the ball, participants were forced into a meta-stable region

of performance where rich and varied patterns of functional movement behaviours

emerged. Participants adapted the organisation of responses, resulting in higher levels of

variability in movement timing in this performance region, without detrimental effects on

the quality of interceptive performance outcomes. Findings provide evidence for the

emergence of meta-stability in a dynamic interceptive action in cricket batting. Flexibility

and diversity of movement responses were optimised using experiential knowledge and

careful manipulation of key task constraints of the specific sport context.


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7.2. Introduction

In complex, degenerate, neurobiological systems, adaptive patterns of movement

behaviour are context specific and dependent on the interacting constraints exploited by

the system (Kelso, 1995). In neurobiology, skilled behaviour can be defined as the

acquisition of a functional relationship between an individual performer and the

environment, characterised by an attunement (sensitivity) to key perceptual variables

(information) and refinement (i.e. adjustment through experience) of movement responses

(Jacobs & Michaels, 2007). From this standpoint, adaptive behaviours are based on

emergent and functional outcomes of indeterminate decision and action processes during

performance and learning (Davids et al., 2006). The adaptive flexibility of skilled human

performance is predicated on neurobiological degeneracy (a technical term describing how

the same performance goal can be achieved through different patterns of movement

coordination), and the capacity to move between different states of organization to satisfy

dynamic performance task constraints; a neurobiological property referred to as

multistability (Hristovski et al., 2006; Kelso, 1995). Edelman and Gally (2001, p. 13763)

described degeneracy as the “ability of elements that are structurally different to perform

the same function or yield the same output.” Degenerate perceptual and action sub-

systems provide a performer with the capacity to contextually adapt actions in dynamic

environments (Edelman & Gally, 2001), supporting transitions between different states of

movement organization (e.g., Kauffmann, 1995). Meta-stable or ‘dynamically stable’ states

allow neurobiological systems to remain in a state of relative coordination with the

performance environment, poised between multiple co-existing states of movement

organisation, ideal for performance in dynamic sports (Kelso, 1995, 2008). Meta-stability

can be observed when a movement system performs under a constant constellation of task

constraints (e.g. distance to a target to intercept) with a specific amount of time available

during which different movement solutions are explored. If, under specific practice task

constraints, the movement system switches to more than one movement solution (stable

attractor), meta-stability is present. If, under changing task constraints, the movement

system remains in an initial attractor and does not transit between solutions, monostability

is present. Meta-stability can be exploited during sport performance when the movement

system suddenly equilibrates to a second movement solution to satisfy changing task goals

(Jeka & Kelso, 1995).

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Therefore, it is an important movement system property, explaining how rich, varied and

creative movement patterns can spontaneously emerge as performers adapt their actions

to achieve particular performance goals (Guerin & Kunkle, 2004). A significant body of

behavioural neuroscience research suggests that meta-stability is central to the way human

brains work (e.g., Tognoli & Kelso, 2009), and is a common feature of effective functioning

complex systems (Kelso, 2008). Some previous work has demonstrated meta-stable

functioning in visual perception (Gross, 1996), rhythmic bimanual coordination (Jeka &

Kelso, 1995), and coordination dynamics in the brain (Tognoli & Kelso, 2009). However,

there have been few attempts to verify meta-stability in movement performance in

dynamic sport environments (Davids & Araújo, 2010). Studies of movement models in sport

are extremely useful because they can provide unique insights into neurobiological control

and organisation of goal directed multi-articular actions under changing task constraints

(Rein, Davids, & Button, 2010), particularly those requiring high levels spatial or temporal

precision (e.g., Renshaw & Davids, 2004).

How might the manipulation of task constraints in performance of multi-articular

interceptive actions allow the identification of regions of stability, and functional

adaptation of movement variability in sport contexts? One study on emergence of adaptive

multi-articular movement patterns and responses in a meta-stable performance region was

undertaken by Hristovski and colleagues (2006). Novice performers were required to

complete a self-paced interceptive action: punch a heavy boxing bag at deliberately

manipulated body-scaled distances to the target. At far distances (e.g., 1-1.2 of the boxers

arm length to target scaled distance) only one action emerged, a ‘jab’. At closer distances

(e.g. 0.3) only ‘uppercuts’ or ‘hooks’ emerged, but at a critical value of scaled distance to

target (0.6), performers were able to explore rich and varied range of movement responses

such as ‘uppercuts’, ‘hooks’ or ‘jabs’. These findings demonstrated how, in this specific

meta-stable region, performers were able to exploit inherent multi-stability based on

system degeneracy (the ability to transit between different stable movement solutions to

achieve a performance goal), allowing a wider variety of affordances (or opportunities) for

action; while at other distances performers had a limited number of performance

possibilities. The findings by Hristovski et al. (2006) were important because they suggested

that in the meta-stable performance region, individuals can assemble and explore

functional and novel movement solutions to satisfy task constraints. Further work is a

needed to investigate candidate meta-stable regions of a performer’s perceptual-motor


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workspace (i.e. the hypothetical map of all possible movement solutions available to a

learner) under varying task constraints in sport.

The study of Hristovski et al. (2006) involved ’novices’ with at least 12 months of training,

suggesting that performers at a more advanced control stage of motor learning (see

Newell, 1985) can exploit system degeneracy when placed in meta-stable regions of

performance. In this stage of learning in dynamic movement systems, noise in the form of

movement variability can play a functional role by enhancing the probability of the

performer transiting between established and stable states of movement organisation,

allowing exploration of multiple task solutions (Schöllhorn et al., 2006). From this

viewpoint, variability (noise) has the capacity to enhance the flexibility of the skilled human

movement system during learning (Schöllhorn et al., 2006), forcing the learner to broaden

the area of search for a functional movement solution from the number of available

options in the learner’s perceptual-motor workspace (i.e. a skilled performer choosing a

movement response to intercept a moving ball with a bat in many different ways).

Hristovski et al. (2006) showed how task constraints (e.g., scaled performance regions)

might be manipulated to lead learners to create and discover new patterns of movement

organization and performance responses. However, there is a need for more research to

demonstrate the existence of meta-stability in performance of multi-articular actions in

dynamic performance environments since the boxing task was a self-paced combat task

performed against a stationary target rather than an opponent. No research has

investigated the existence of meta-stability under externally-paced task constraints in a

representative task requiring performers to co-adapt their actions with an opponent. This is

an important distinction, since presence of an opponent increases uncertainty for

performers and constrains them to use probabilistic perceptual judgments for decision

making (Jackson & Morgan, 2007), rather than self-directed actions (e.g., using the

biological movement of an opponent to predict the pitching location of a ball to be

intercepted – a critical feature of success in fast interceptive actions).

Here, we present data of behavioural responses (movement timing and performance

responses) in multi-articular interceptive hitting actions under carefully manipulated task

constraints imposed by differences in ball pitching location. The aim of the study was to

examine how meta-stability could be exploited for performance enhancement in externally

paced interceptive actions in fast ball sports, such as cricket batting. It was expected that

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relatively skilled individuals at the control stage of learning could exploit system

degeneracy, and functionally adapt their movement responses (e.g., multi-stable

movement solutions or shot types). In this way, analyses of movement timing (i.e.

functional variations in key temporal components of multi-articular actions) can provide

insights into the stability of the specific ‘attractors’ (stable and functional patterns of

organisation) under varying task constraints. Based on the methods of Hristovski and

colleagues (2006), it was anticipated that a candidate meta-stable region would emerge at

a particular body-scaled ball pitching location; a pitching location requiring one of two co-

existing initial movement responses, with a step towards (forward) or away (back) from the

approaching ball. In the task of cricket batting, this ball-pitching region was identified a

priori as a potential meta-stable region based on experiential knowledge (Woolmer et al.,

2008), and performance observations. Cricket bowlers attempt to pitch the ball in this

location (see Figure. 1: region 3) to create uncertainty for batters by exploiting the co-

existence of two functional movement responses (i.e., batters are unsure whether to move

forward or back). In the candidate meta-stable region, it was expected that more

movement timing variability would emerge as batters adapted their actions to ensure that

quality of performance outcomes were maintained under changing task constraints.

7.3. Method

Participants

Six participants (Batters: mean age 16.32 ± 0.30 years) with a mean of 8.83 ± 1.72 years of

competitive junior cricket experience were recruited for the study, and were matched on

anthropometric characteristics (mean height: 1.76 ± 0.04 m). Batters were matched in

height to allow for standardised body-scaling of ball pitching regions. Participants had

received similar amounts of task-specific practice, and could be considered to be

moderately skilled junior performers, adjudged by 2 Cricket Australia Level 3 coaches and

motor learning specialists to be in the control stage of motor learning for this task (Newell,

1985). Due to bowling workload concerns in attaining required number of trials each batter

faced three bowlers (mean age: 15.25 ± 0.99 years). Bowlers had similar conventional

bowling (ball delivery) actions and physical attributes (peak height of bowling arm: 2.10 ±

0.05 m; mean bowling speed: 28.29 ± 0.96 m·s-1). Peak height was measured from a sagittal

view of the bowling line. Ball speed was assessed using a sports radar gun (Stalker Radar,

Texas). One batter was later removed from the analysis due to not completing the required


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number of shots in each of the performance regions. All participants wore full protective

equipment and provided informed consent, with ethical clearance obtained through a

university ethics committee.

Procedure

Data collection took place in the participants’ regular practice facility. Four spatial target

regions (0.5 x 1 m - see Figure 7.1) for ball pitching location (bounce point) were created in

order to require batters to step both forward and backwards to intercept balls. Regions

were body-scaled to the batters’ stature, and based on accuracy levels achievable by

developmental bowlers, allowing for consistent and standardised target areas during data

collection. Three of the performance regions (see Figure 7.1) were based on typical ball

pitching locations focused on during batting skill development (Woolmer et al., 2008):

region 1) ball pitching close to the batter affording a front foot shot (2.5-3.5 m from the

stumps), region 2) ball (5-6 m) bouncing to the height of the top of the stumps (bowlers’

target in cricket), also requiring the batter to move forwards, and region 4) ball (8-9 m)

bouncing higher, typically requiring a batter to move backwards to intercept the ball. A final

performance region was created between regions 2 and 4, predicated on experiential

knowledge as forcing participants into a region of greater uncertainty for response

organisation (candidate meta-stable region 3: 6.5-7.5 m). The use of four performance

regions was chosen to provide insights into the stability and variability of movement timing

in well practiced movement patterns (for example, a ball pitching in regions 1 and 2 are

practiced almost exclusively in the early stages of movement organisation for this type of

interceptive task, and heavily throughout developmental stages in cricket).

Batters faced bowlers in rotation, reminiscent of a standard practice session. Batters were

instructed to perform as they would in a competitive performance context, by attempting

to score as many runs as they could while avoiding being bowled (ball hitting stumps). No

further instruction or knowledge of the experimental aims was provided. Batters continued

to bat until they had completed 5 trials in each of the performance regions (due to

programme limits on junior bowler workloads). Each bowler followed a randomised script

for ball pitching locations to target. Ball pitching location was noted during collection by

two experienced researchers and accuracy of this judgement was later confirmed

independently by the two researchers before analysis of movement data from video

capture. Two event-synchronised video cameras (Casio EXILIM Pro EX-F1: 60 Hz)

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concurrently captured participants’ movement organisation and moment of ball release for

frame by frame analysis. A third camera (Sony HVR-V1P, 50 Hz) was positioned behind the

batter to provide shot classifications.

Figure 7.1. Side and above views of experimental setup. Performance regions are numbered with

respect to distance of ball pitching from batter.

Analysis

Batters’ movement responses were analysed by two skill acquisition specialists, who were

also qualified Level 1 and 2 cricket coaches. Shot type (by direction) and movement

response (gross movement of the batter forwards or backwards) were recorded and

grouped by performance region. Mean number of different cricket shots (classified by

direction) were calculated for the four distinct performance regions. Measures of quality of

bat-ball contact (QoC), validated by Müller and Abernethy (2008), and forcefulness of bat-

swing (an estmation of the attacking or defensive intent of the interceptive response; FoBS,

see Mann et al., 2010) were used as simple but reliable tools for assessing interceptive

success. A trained observer provided a QoC and FoBS score for each trial in line with the

validated measures. QoC scores were defined as: (1) the ball contacting the bat and

travelling in a direction consistent with the pre-contact plane of bat motion/ swing (2

points), (2) the ball contacting the bat but deflecting in a direction inconsistent with the

pre-contact plane of bat motion/swing (1 point), and (3) the (missed) ball not making

contact with the bat (0 points). FoBS scores were defined as: (1) a complete follow-through



Batter1 2 3 4

Bowler

Stumps3.5 m6 m

7.5 m9 m

Ball Release

0.71 m

Performance regions


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of bat-swing after point of bat–ball contact (2 points), (2) an incomplete follow-through of

bat-swing after point of bat–ball contact, and (3), no follow-through of bat-swing after

point of bat–ball contact, or no attempt is made to hit the ball. Reliability was assessed on a

selection of 20 random trials (20%). Intra-rater reliability was assessed by comparing two

video reviews (with a 4-week break) of the first observer, while inter-rater reliability was

assessed by comparing the scores of the first observer with those of a second observer.

Strong correlations were found for both intra- (rs = .85) and inter-rater (rs = .90) reliability,

consistent with previous work (Mann et al., 2010).

After previous work, key phases of the batters’ actions were identified as: (1) point of ball

release, (2) initiation of backswing of the bat, (3) initiation of first movement of the front or

back foot (e.g., the definitive movement forwards or backwards), (4) initiation of the

downswing of the bat, (5) placement (planting) of the front or back foot, and (6), point of

bat–ball contact (Pinder, Davids, et al., 2011a). Moment of ball release was recorded as the

first frame after the ball had left the bowler’s hand. Foot movement initiation and

placement were defined as the first frame after the foot had lifted off and been placed on

the ground, respectively. Initiation of backswing and downswing were identified by an

experienced researcher using frame-by-frame analysis (see Pinder, Davids, et al., 2011a).

Group means of each batter’s standard deviation measure (SD) at each phase of the multi-

articular action were used to estimate variability of temporal performance aspects (Fleisig,

Chu, Weber, & Andrews, 2009). Separate one-way within-participants ANOVAs with

repeated measures were used to analyse the data on all dependent measures. In the (one)

case of violation of the sphericity assumption, a Greenhouse–Geisser correction was used

to adjust the degrees of freedom for treatment and error terms of the repeated measures

variables in the ANOVAs. Following these analyses, post-hoc pairwise comparisons were

undertaken to assess which comparisons were statistically significant in each instance.

Bonferroni adjustments were used in all cases to control for type I error resulting from any

interdependence within dependent measures. Finally, partial eta-squared (ηp2) values were

provided for each ANOVA to provide an indication of the effect size or magnitude of the

differences in variability. Given that recent insights in behavioural sciences have

demonstrated how the tendency to average performance data for statistical analysis can

mask functional variability observed in individual participants (see Newell, Liu, & Mayer-

Kress, 2001), results were assessed on an individual basis in addition to group analysis.

Exemplar data are used to illustrate the variability in movement timing variability identified

using inferential statistics.

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7.4. Results

Figure 7.2 provides a pictorial representation of the performance responses, including types

of interceptive response by direction, and primary movement of the batter (e.g., forward or

backwards before time of interception). Individual batters’ interceptive actions (e.g., shot

direction) were highly varied when balls pitched in the candidate meta-stable performance

region (region 3: mean number of different types of shots: 4.60 ± 0.5), when compared to

region 1 (2.20 ± 0.4), 2 (2.00 ± 0.7), and 4 (2.4 ± 0.8). Batters completed all trials in regions 1

and 2 with a primary or gross movement forward, and all trials in region 4 with a backwards

movement response. Conversely, batters, when placed in the candidate meta-stable

performance region (3), demonstrated 48% front foot responses, and 52% back foot

responses (see Fig. 2). It should be noted that in this region, some back foot shots were

played to balls pitched nearer to the batter, while some front foot shot were played to balls

that were pitched further away (i.e., there was not a line across the middle of this region

where batters played front foot shots on one side and back foot shots on the other).

Figure 7.2. Pictorial representations of types and consistency of movement responses (i.e. shot by

direction and batters’ primary movement) in four distinct performance regions categorised by ball

pitching location. Note: lines indicate shots categorised by type, and are intended to demonstrate

consistency and number of responses. Figure and response outcomes are not to scale.

There were no significant effects of pitching location on either QoC scores, F(3,72) = 1.48, p

> .05, ηp2 = .06, or FoBS scores, F(3,72) = .43, p > .05, ηp

2 = .02. Both quality and

intentionality of the action (QoC: 1.64 ± .63; FoBS: 1.36 ± 0.48) when responding to balls

1 2 3 4

Front foot response

Back foot response


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pitched in region 3 were reflective of the scores observed in region 1 (QoC: 1.92 ± .28;

FoBS: 1.52 ± .71), 2 (QoC: 1.68 ± .69; FoBS: 1.36 ± .57) and 4 (QoC: 1.76 ± .52; FoBS: 1.36 ±

.64).

All batters showed highly stable movement timing in regions 1, 2 and 4 as evidenced by low

standard deviations in initiation times, but greater movement timing variability when balls

pitched in the candidate meta-stable performance region 3. Figure 7.3 shows exemplar

data for comparisons of movement timings of the unfolding interceptive responses (5 trials

per target region) of two batters (B2 and B4). In this way, data demonstrated movement

coupling between upper and lower extremity responses utilised by individuals (e.g., in

comparing the different functional movement timing strategies of B2 and B4 in region 4),

and provides an assessment of the stability of movement organisation in distinct

performance regions (e.g., amount of variability across multiple trials).

Both backswing, F(3,12) = 15.19, p < .01, ηp2 = .79, and downswing timings, F(3,12) = 13.94,

p < .01, ηp2 = .78, were significantly affected by performance region, with higher variability

in initiation times when balls pitched in the candidate meta-stable region 3, compared to

regions 1, 2 and 4 (all p < .05). Furthermore, initial timing of foot movement (e.g.,

demonstrating a decision to move forward or back), F(1.17,4.68) = 8.80, p < .01, ηp2 = .69,

and final foot placement, F(3,12) = 101.35, p < .01, ηp2 = .96, were significantly affected in

region 3, with greater amount of movement timing variability present when compared to

other performance regions (all p < .05). Figure 7.4 shows estimations of variability in timing

of the four key movement components, with the greatest variability typically occurring in

the later phases of the interceptive action (e.g., final foot placements: ηp2 = .96).

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Figure 7.3. Unfolding movement organisation for; a) Batter 2 and b) Batter 4, in 4 distinct

performance regions. Region 3 represents the candidate meta-stable performance region. BR = ball

release, BS = backswing initiation, IFM = initial foot movement, DS = downswing initiation, FFP = final

foot placement.

0

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a)

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1 2 3 4


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Figure 7.4. Estimations of variability (SD) of key movement initiations during the unfolding

interceptive action for 5 skilled junior performers (batter 1-5 from top to bottom) in 4 distinct

performance regions. Region 3 represents the candidate meta-stable performance region. BS =

backswing initiation, IFM = initial foot movement initiation, DS = downswing initiation, FFP = final

foot placement

0.00

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of c

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7.5. Discussion

This study attempted to verify how manipulation of specific task constraints in an

interceptive action in cricket might identify a ‘meta-stable’ region of performance which

shaped the emergent movement patterns of participants. Data presented here support

previous investigations of meta-stability in performance of multi-articular actions in sport.

(Hristovski et al., 2006). Experiential knowledge and careful manipulation of task

constraints helped us identify these performance regions in the cricket batting context

(characterised by stability, and periods of functional adaptability). In our study, movement

organisation spontaneously emerged at each ball pitching location as affordances for action

changed (actions that the batter perceived were possible or required). Results

demonstrated how targeting candidate meta-stable regions could provide insights into how

performers organise responses for goal directed actions. Highly stable movement patterns

observed in specific performance regions (e.g., movement timing and performance

responses in regions 1, 2 and 4) exemplify system attractors (e.g., repeatable, information-

movement coupled responses). In these regions, these participants demonstrated stable

patterns of movement timing, due to extensive experience of blocked and repetitive

practice during their development (see Figures 7.3 & 7.4). Furthermore, in these regions,

batters’ selection of movements and shot types were highly consistent, as evidenced by a

limited range of performance outcomes (e.g., in regions 1 and 2 all batters played

exclusively with forward movements, and with a narrow range of shot types either side of

the bowler). Our data showed that forcing a performer into a potential meta-stable region

allowed the spontaneous emergence of rich patterns of movement organisation and

performance responses (Hristovski et al., 2006). In this region, skilled individuals can more

easily perceive alternative options and adapt movement patterns to changing task

constraints. Data showed that, when batters were placed in this region, they were able to

exploit fluctuations in ball delivery and adapt the timing of key components of the

movement system more easily to provide functional performance outcomes. Higher levels

of variability were present for all 5 batters (see Figure 7.4), demonstrating that all

participants were similarly affected by the dynamically stable task constraints and able to

functionally adapt movement timing in this candidate meta-stable performance region.

Furthermore, it might be suggested that high variability in the later stages of the actions,

such as the point of downswing or placement of the foot, are a product of small movement

differences emerging at earlier stages of the action. It is worth noting that all performers in


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this meta-stable region were able to provide the same quality of interceptive response,

with no significant differences between bat–ball contact (QoC) or intentionality scores

(FoBS) when compared to regions 1, 2 and 4. Additionally, in this region performers had a

wider array of performance outcomes (i.e. shot directions – See Figure 7.2), demonstrating

an ability to direct interceptive shots to the same locations with different primary

movements. In this region, there was an equal likelihood of a performer moving forwards

or backwards (48% and 52%, respectively). This finding highlights how two very distinct and

co-existing initial movement responses exist, and provides support for our view that a ball

pitching in this region forces performers into a meta-stable region of batting performance.

Very little research has focused on the concept of meta-stability in the assessment of

organism-environment behaviours beyond simple bimanual actions. As previously

discussed, one exception is a study by Hristovski and colleagues (2006), in which

performers demonstrated specific performance responses emerging at different body-

scaled distances from a heavy punching bag. Body-scaled ball pitching location was

observed in the current study to act as a control parameter between states of movement

organisation in this interceptive batting task, in much the same way as the distance from

the stationary target was found to be critical in the boxing task. The distance that the ball

pitched in front of the batter had a significant effect on movement timing variability,

performance responses and emergent affordances for action (e.g., opportunities for

different shot types), echoing results reported by Hristovski et al. (2006). Taken together

the data suggest that significant increases in variability of movement timing and

performance responses should be expected when performers are placed in a meta-stable

region. This type of movement variability is functional, reflecting how performers explore

the available perceptual-motor workspace (i.e. the hypothetical map of possible movement

solutions available) and should not be construed as performance error. Instead, patterns of

functional movement variability need to be interpreted with respect to consistent

performance achievement. These participants at the control stage of learning

demonstrated how stable patterns of movement organisation could be functionally

adapted to provide consistent performance outcomes. Harnessing system degeneracy

allows for learners to trade-off stability (specificity in movement control) and instability

(diversity) under changing task constraints to become highly adaptive and successful

decision makers (Edelman & Gally, 2001). In the meta-stable region performers can

function neither completely dependently on environmental information to regulate actions,

nor completely independently. Utilising experiential and empirical knowledge to seek and

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identify meta-stable performance regions which enhance exploratory activities, could lead

to greater understanding of behavioural organisation in complex neurobiological systems.

In the current study, well learned performance responses emerged in regions 1 and 2 (ball

pitching locations closer to the batter) demonstrating how the search for movement

solutions is likely to end up at the most stable movement system attractor. Critically, the

deepening of particular attractors (through highly repetitive practice) may increase the

likelihood of a learner ignoring other co-existing performance options. The practice strategy

of acquiring highly stable movement patterns during repetitive practice may become

dysfunctional in a competitive performance context if counteracted by an opponent (a

process called co-adaptation in sport). In understanding this process, opposition teams

could use areas of stability and instability in batters performances to exploit potential

weaknesses in competitive situations; this is a rich area for future applied work. The results

here showed that placing learners in meta-stable performance regions creates adaptive

flexibility and functional variability in their timing and performance responses. (Hristovski et

al., 2009). This type of variability can provide the basis for co-adaptive moves by a learner in

sport, amplifying the exploratory nature of the process and can aid the discovery of

functional and individualised solutions to a specific task goal (Schöllhorn et al., 2009).

7.6. Conclusion

We provided data to demonstrate how manipulation of task constraints can create regions

of meta-stability in sport performance contexts. Performance analysis of cricket batting

demonstrated how individuals at the control stage of learning exploited system degeneracy

and multi-stability to functionally adapt stable movement patterns to satisfy changing task

constraints. Meta-stability, and thus flexibility and diversity of performance responses, can

be optimized using experiential knowledge and careful manipulation of key task constraints

in a sport context. Designing research and practice tasks which focus on candidate meta-

stable regions result in rich and varied patterns of movement organisation and

performance responses, and may allow for the development of better decision makers

Results of this study showed that performers who have a large degree of control over

motor system degrees of freedom can harness system degeneracy and meta-stability to

achieve adaptive and successful performance in dynamic sports contexts. Questions remain

over the presence of meta-stability in novice and highly skilled populations, a rich source

for future experimentation. Future research should focus on establishing an understanding

of how meta-stable regions of performance emerge and decay throughout the learning


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process, using detailed analyses (e.g., 3D motion analysis), and under various task

constraints. For example, it may be that the speed of the approaching object (e.g., ball to

be intercepted) and skill level mediates the ‘size’ of the meta-stable region. This may allow

practitioners to enhance the design of learning environments (Hristovski et al., 2009).

Chapter 8 - Epilogue

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Chapter 8 – Epilogue

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8.1. Introduction

The overarching aim of this thesis was to demonstrate the importance of representative

design for both experimental and learning contexts in sport. The use of a movement model

from a sport performance context not only allows for the advancement of theoretical

understanding of human behaviour, but provides methodological implications for sports

science research, and practical guidance in cricket batting.

As outlined in the introduction (see section 1.3), the programme of research concerned a

conceptual, theoretical and methodological approach aimed at enhancing our

understanding of the acquisition and performance of perceptual-motor behaviour in

dynamic interceptive actions. The research presented (Chapters 3-7) examined emergent

performance from an Ecological Dynamics perspective, providing theoretical and empirical

advances in our understanding of how the manipulation of ecological task (i.e.

informational) constraints affect the control of movement organisation of cricket batter’s

actions. Modelling the performer as a complex system using theoretical concepts

emanating from Dynamical Systems Theory (DST) and Ecological Psychology allowed for

unique insights into current understanding of perception and action in sport. Importantly,

the movement model used throughout this programme of work (e.g., interceptive skill in

cricket batting) exemplifies the functional relationship between perception and action, with

empirical findings demonstrating how the design of experimental or learning tasks has

significant effects on the performer-environment relationship. Importantly for this thesis,

the research findings demonstrate that representative design of experimental task

constraints is a critical concern in effectively capturing performer-environment

relationships in experimental psychology, sport science and, specifically, perceptual-motor

behaviour in fast ball sport. Methodologically the results demonstrate the importance of

ensuring that experimental task constraints are representative of the performance context

of interest. On a practical level, the findings provided coaches with an opportunity to target

perceptual training using specific video-simulation designs, and provided cautionary

evidence for the overuse of ball projection machines in training situations. Here, we review

the contribution made at each stage of this thesis and reiterate the important theoretical,

methodological and practical implications of the PhD programme.


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8.2. Phase one

The first phase of this thesis provides a review of previous literature pertinent to the

research questions, and demonstrates the development of a research problem; a problem

outlined for psychological sciences by Egon Brunswik (Brunswik, 1956) more than half a

century ago, and more recently highlighted in fast ball sport through advances in

behavioural neuroscience (van der Kamp et al., 2008). A major concern in studies of

perceptual-motor expertise, particularly in sports science, was (and still is) the reductionist

experimental designs utilised by some researchers. Specifically in studies that have utilised

cricket batting as the task vehicle, the ubiquitous use of ball projection machines, video and

occlusion presentations, and simple non-representative response requirements, have

demonstrated that the methodological concepts introduced in this phase of the

programme of work were essential to further understanding of perceptual-motor skill in

fast ball sport. The removal of representative action requirements in experimental design is

currently limiting or even misleading understanding of perceptual-motor skill in sport.

Findings from this phase of the research provided evidence for the concern of generality of

performance data from experimental and learning tasks to those tasks representative of a

performance context of facing a ‘live’ opponent. The results of this work (see Chapter 3)

revealed significant differences in the performance and movement characteristics of

developmental cricket batter’s actions under changing task constraints: those of a

representative task of facing a ‘live’ bowler, a life-size video simulation, and a ball

projection machine. Results demonstrated that batters were able to functionally adapt

behaviours for each specific task highlighting the degenerate nature of skilled human

movement systems (also see Davids & Araújo, 2010; see Edelman & Gally, 2001). The

findings show that the removal of key perceptual variables, pre- and post-ball release,

suggests that researchers should ensure that they effectively capture the perception-action

coupled responses when designing experiments in perceptual-motor studies. Failure to

ensure the presence of key information sources through sampling performance

environments leads to experimental designs that diminish the generality of research

findings. Differences in a batter’s movement organisation were present even when

‘coupling’ of a batting response to the life-size video simulation. Previous research which

has utilised micro-movements, or even verbal or pen and paper responses, are therefore

concerning based on recent advances in our understanding of the complimentary

contributions of perceptual and action sub-systems (see van der Kamp et al., 2008). Despite

this, in this thesis it was demonstrated that batters were able to achieve the same temporal

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advantage under video simulations conditions as they were against the bowler. Batters

demonstrated comparable early movement organisation based on the inclusion of

advanced and early ball flight information (even when presented on a screen in 2D). Using

the concept of action fidelity to compare between experimental tasks allowed us to show

that high quality video simulations with accompanying coupled movement responses could

provide representative performance tasks for the assessment of affordance perception in

this specific task, with a higher fidelity of early action against a video simulation than

against a ball machine where actual interceptive action occurs (participants actually

intercept a ball). Practically, coaches could provide life-size video simulations to allow

performers to attune to specific aspects of an opponent if, i) they have not experienced a

situation before (e.g., safety and fast ball speeds), or ii) if they have limited access to

opponents and do not wish to rely on ball projection machines.

Research outputs generated in this phase (e.g., Chapter 3) advanced understanding in

experimental psychology by specifically demonstrating the benefit of using task vehicles in

sport under careful manipulation of informational constraints (Pinder, Davids, et al.,

2011a), and demonstrated the practical implications from a constraints-led approach to

motor learning and nonlinear pedagogy (Pinder, 2010). Further work in assessing video-

based learning designs was beyond the scope of the current programme of work, and is a

rich area for researchers to target. It is also currently unknown if the results of the work

presented in this thesis when comparing bowler and video simulation tasks would be

replicated with higher skilled performers, however, previous research findings and

experiential reports suggest that similar findings would be expected in more elite

populations (Renshaw & Chappell, 2010; Renshaw et al., 2007). Future work should focus

on looking at changing similar task constraints evidenced in this work across various skill

levels throughout the developmental pathway, and assess the efficiency of using life-size

coupled video simulations to enhance affordance perception, more than simply measure it.

The prominence of ball machines in experimental and practice design was of greater

concern, particularly given their high usage with developmental level performers (see

below). Furthermore, researchers should look to enhance understanding of the control of

action in competitive performance contexts (e.g., through the use of accelerometers and

gyroscopes); it is acknowledged that lower frame-rates used at stages of this programme of

work may be a limitation in discovering even finer aspects of control of performers actions

and visual strategies. Logistical (available equipment) and technological (Mobile eye

capturing rate) restrictions limited these aspects; nevertheless further work would help to


153

support and further our understanding in this area. The current work was limited to a 2D

planar analysis of the organisation of two common performance responses in cricket

batting, based on previous research (Renshaw et al., 2007; Stretch et al., 1998). A saggital

plane analysis was suitable for the aspects measured, however, limited the research to the

assessment of planar movements only. It is acknowledged that any deviations out of this

saggital plane may have resulted in small errors in measurement of foot movement or bat

height. Any trials where this was suspected to have occurred were removed from the

analysis. Future research should now look to assess a range of performance responses using

3D motion capture techniques (particularly in assessing the use of video simulations for

affordance perception – see Chapter 3) to support or extend the findings of this work.

As discussed (section 3.5), the first stage of understanding skilled performances in

interceptive actions must be to accurately measure and describe the specific task

constraints that effectively capture the perception-action coupled responses, before

describing or assessing how performers acquire knowledge and skill within that context

(Araújo & Davids, 2009; Fajen et al., 2009; Pinder, Davids, et al., 2011b). This phase of the

PhD programme has demonstrated that many experimental designs utilised in perceptual-

motor research in sport have not ensured that performer’s responses are based on

information sources representative of the performance context of interest. It is feasible,

therefore, that experimental designs are currently limiting or misleading our progress in

understanding skilled performance in fast ball sport. It is acknowledged that research is

needed to clarify whether these findings would be replicated with elite level performers. It

may be that at the extreme ball speeds recorded in elite fast bowlers (e.g., 140 k·m-1), ball

flight becomes the salient information used by elite performers to regulate their batting

actions. Further research is needed to assess the effects on skill acquisition of different

volumes (amount of time) of supplementary practice in fast ball sports (e.g., visual training

through video simulation designs or ball projection machines) at various skill levels

throughout the developmental pathway.

However, during the first experimental phase of this programme of work, a number of

research articles from other research groups emerged that utilised the specific task

constraints for experimental designs that this thesis aims to address: perception in cricket

batting (Weissensteiner et al., 2009a; Weissensteiner et al., 2008). Given the findings of the

first phase, and the continued use of ball machine and video-based designs in empirical

research , it became apparent that previous attempts to raise concerns about the need to

154

underpin experimental design with Brunswick’s ideas were not being taken on board by

sport scientists and practitioners (see Araújo et al., 2007; Dicks et al., 2008). While some

researchers have begun to recognise the importance of the functional coupling between

perception and action due to expertise effects under various levels of coupling, the lack of a

theoretical rationale supporting such research is also concerning. Therefore, the second

phase of the research aimed to develop a comprehensive theoretical framework to

describe the importance of the methodological concept of representative design for

experimental and learning design in the sport sciences.

8.3. Phase two

The theoretical framework is presented in Chapter 4 of this thesis and specifically targeted

a wider sports science audience. The paper was the first theoretical position published in

the Journal of Sport & Exercise Psychology in a decade and demonstrates the important

contribution the ideas generated have made to the area. The integration of Gibsonian and

Brunswikian concepts allowed for the development of a more comprehensive and

principled theoretical framework than either theoretical position may have provided in

isolation (Warren, 2006). The framework allows sport scientists, practitioners, and

pedagogues to assess whether the experimental or learning design has ‘attained

representative design’; essentially do the task constraints used to study perception and

action processes in sport allow participants to pick up and use information from the

environment to support functional movement responses? Representative learning design is

therefore a contribution to the extant literature which theoretically captures how sport

scientists can use insights from ecological dynamics to ensure that experimental and

practice task constraints are representative of the particular sport performance context to

which data are expected to be generalized toward. Furthermore, we reiterate the

distinction between Brunswikian terms to allow for the acknowledgement of Brunswik’s

(1956) original insights and harnessing of potential benefits of the methodological concept

of representative design.

The strength of these theoretical advances are evident in the adaptability of the concepts

for a variety of distinct areas of sports science, in addition to the global framework

presented (Pinder, Davids, et al., 2011b). For example, during the emergence of this thesis,

it became apparent that specific sub-disciplines of sport science such as talent identification

and development face similar theoretical and methodological problems to those outlined in


155

Chapter 4. More specifically, the concepts emanating from this ecological dynamics

approach were used to develop a principled theoretical framework to guide future

experimental and practice design for the use of ball projection machines in fast ball sport

(Chapter 5). In this paper, we specifically questioned and reviewed the extant literature

regarding ball projection machines in sports research and performance preparation. This is

not a trivial issue, since not only do they reduce the possible injury incidence in adolescent

bowlers, but are considered to aid the development of batting skill in fast ball sport, despite

initial evidence proposing significant differences in the acquisition of interceptive responses

between live bowler and ball machine contexts (Pinder et al., 2009; Renshaw et al., 2007).

The use of ball machines is an extremely common practice in both research and practice

(Cork, Justham, & West, 2008; Croft et al., 2010; Land & McLeod, 2000; D. L. Mann et al.,

2007; Renshaw & Chappell, 2010; Weissensteiner et al., 2009a; Woolmer et al., 2008), and

there was a need to provide guidance to practitioners and scientists for their future use. As

we do concede (see section 5.6), the research in this specific area may be regarded to still

be in its infancy, and we suggest a number of areas which require further attention

(including the work presented in phase three – see below). However, in questioning the

role of ball projection machines in the first instance we have provided a significant

methodological advancement to the area. The following quote demonstrates how ball

projection machines are still considered to be appropriate and highly beneficial tools for

the preparation of elite performers:

“Ponting, however, has left no stone unturned in his bid to rediscover his form,

spending at least an hour-and-a-half batting in front of a bowling machine

under the watch of coaches Dene Hills and Justin Langer.”

(Wu, 2011)

The position paper (Pinder, Renshaw, et al., 2011) that forms the basis of Chapter 5

succinctly reviews the experiential and empirical extant literature in the use of ball

machines, and develops a highly usable model (see Figure 5.1) for practitioner coaches, in

addition to experimental situations. An important aspect of a PhD programme such as this

is dissemination of the research to sports practitioners and so far the findings of the first

and second phase of this PhD programme have been disseminated through the Cricket

Australia Elite Coaches network, with work presented to high level coaches in Australia,

New Zealand and England. Gratifyingly, very positive feedback has already been personally

received from academics, skill acquisition specialists and coaches (via personal

156

communication) and highlights that future work should look to use this model to assess the

use of projection machines across other task constraints, sports, and in more varied athlete

population (e.g., levels of skill). Future empirical and theoretical advances should consider

additional aspects beyond informational constraints in performance environments, such as

psychological factors (e.g., emotion) and learning goals.

8.4. Phase three

Over the first two phases of this thesis, a theoretical, conceptual and methodological

problem was highlighted, with comprehensive principled frameworks outlined to guide

future experimental and learning designs. Here, in the third phases of the research, we

firstly provided further evidence in the comparison of ball machine and ‘live’ bowler

situations, before demonstrating how the careful manipulation of task constraints can

provide excellent insights into the role of meta-stability in human performance of a

representative sports performance task.

In Chapter 6, visual strategies of batters under both ball machine and ‘live’ bowler

conditions were assessed and compared. This is a critical advance for the research area,

given that our previous understanding of how performers cope with temporal demands in

fast ball sport (specifically cricket) were based predominantly on artificial task constraints

of ball projection machines. Here, we demonstrated similar findings for developmental

performers when facing a ball projection machine; however, visual strategies were

significantly different when batters viewed a ‘live’ bowler projecting a ball. In comparing

the fidelity of visual pursuit and saccade variables across both task constraint and relative

skill level (within a developmental squad), it was demonstrated that the relationship

between the pursuit track initiation and duration, and the presence and timing of a visual

saccade, is not consistent with previous interpretations when transferred to the

performance context of facing a bowler. Batters pursuit tracked the ball sooner after

release, and for a greater duration of early ball flight against a bowler, requiring fewer

visual saccades (a finding consistent among all batters). Furthermore, Chapter 6 provides

evidence for the specific differences in visual performance of batters of relatively different

skill levels, even within the same performance squad. Using a combination of both within-

task and coaching rankings ensured that we were provided with a representative

assessment of their current skill level. It was demonstrated that top order (higher skilled)

players from a respected Australian school 1st XI initiated the pursuit track earlier, a finding


157

generally consistent even across different task constraints. These differences were also

more pronounced when facing a ‘live’ bowler, the condition under which batters’ skill level

is ultimately tested. Additionally, a critical advancement to the area of research was that

higher skilled batters made fewer visual saccades across all conditions, again a finding more

distinct when facing a bowler. This appears to be in stark contrast to previous work (Land &

McLeod, 2000), in which expertise was seen to be characterised by early visual saccades (it

should be noted that no previous work has discussed the percentage of saccades across

trials). An early saccade was not shown to characterise skilled performance in

developmental performers, particularly when completing a representative task.

While research assessing the fidelity of visual performance between distinct experimental

task constraints was required in the first instance, researchers should now focus on

confirming these findings in a comprehensive assessment of visual strategies across a range

of skill levels (e.g., throughout the developmental pathway) under representative task

constraints. A limitation of the measurements used in this phase of work was the low frame

rates provided by the Mobile Eye tracker (25Hz), where increased frame rates (i.e.

sensitivity) may reveal important differences between the visual tracking and identification

of ball bounce that were not identified in the current work. There is also a need to link

visual and movement aspects of interceptive performance, which has received little

research attention (see Panchuk & Vickers, 2006 for an exception). Nevertheless, this work

(Chapter 6) provided some initial evidence to extend previous interpretations of visual

strategies in fast ball sport (Croft et al., 2010; Land & McLeod, 2000), and demonstrated the

methodological and practical implications of using ball machines in athlete preparation.

Requiring batters to perform under representative constraints of facing a bowler also

revealed some very interesting and significant findings relating to how performance

emerges and is controlled under changing task constraints; allowing for advances in our

understanding of skilled multi-articular interceptive actions from a dynamical systems

perspective (see Chapter 7). Using unique coaching insight into the specific cricket task, and

under careful experimental manipulation (creation of performance regions), this research

programme provided only the second empirical study to demonstrate the presence of

meta-stability in movement models in sports performance (see Hristovski et al., 2006), and

the first to demonstrate this important concept under co-adaptation with a ‘live’ opponent.

Cricket batters demonstrated diversity and flexibility under careful manipulation of task

constraints. It was apparent that performers who have a good degree of control over their

158

actions in interceptive tasks can harness system degeneracy and meta-stability to provide

adaptive and successful performances, even when two very distinct co-existing responses

exist (e.g., to move forward or back). Future research should strive to demonstrate how

targeting meta-stable performance regions affect the acquisition and refinement of

interceptive and decision-making behaviour in sport. It is possible that, at later stages of

learning, ball projection machines could be used to locate the learner in a meta-stable

region of a perceptual-motor workspace. In this region, learners remain in a state of

relative coordination with the practice environment, being unable to function completely

independently, nor dependently, on environmental information to regulate their actions.

By accurately projecting the ball into specific locations, more advanced learners can be

forced to enter meta-stable regions to enrich adaptive performance behaviours during

practice.

It is important to note that a critical aspect of this work (in particular Chapter 7) was that

required behaviours were not prescribed to the batters in each study. As such, batter’s

actions were, as was the PhD process, emergent in nature. It is important that researchers

provide an acceptable degree of control over experimental design, but should not limit the

possible analyses or consideration of emergent factors. The batters in this work (Chapter 7)

demonstrated well practiced responses (i.e. performance attractors) to balls bouncing in

specific locations, which tended to overwrite their search for other possible responses. This

is an important issue since batters may gravitate toward these well practiced attractors,

and therefore reduce the amount of flexibility and diversity of performance responses

resulting in less creativity in their batting and hence limiting their potential. Future work

should look to expand upon this initial investigation, and demonstrate how meta-stable

regions emerge and decay throughout the learning process, or change across skill level.

Movement timing variability was adequately captured in this programme of work (60 Hz),

however, higher frame rates may allow for the identification of key differences in the

control of individuals’ movement responses. It is also acknowledged that this initial

exploration was also limited by simple performance and movement assessments due to the

inclusion of all possible performance responses (e.g., not simply planar responses – see

Chapter 3); a more comprehensive and detailed analysis should now be completed to

consolidate and extend the findings of this programme. However, we have provided a first

stepping stone for a rich area for future research. The first task for future work must be for

researchers to assess if the targeting of meta-stable regions can increase decision-making

behaviours and skilled performance in representative performance contexts in sport.


159

8.5. Conclusion

This PhD programme contributes to the integration of Bruswikian concepts, providing

evidence for the importance of representative design in the sport sciences, with principled

theoretical frameworks for practitioners to use to guide future work. Practitioners should

ensure that research and practice designs allow for performers to pick up information

sources from the performance context of interest to allow for functional, representative

perceptual-motor behaviour, and consider how the manipulation of practice task

constraints may be used to enhance learning design.

Appendix – The changing face of practice in cricket batting

161

Appendix - The changing face of practice in cricket batting

The following pages contain a book chapter that demonstrates the practical implications of

the first phase (Chapter 3) of this PhD programme of work. The chapter is focussed on a

constraints based understanding of coaching cricket batting, and highlights the possible use

of ball machines and video simulations in developing batting skill. The chapter was

internally reviewed before publication in:




halla

Due to copyright restrictions, this published book chapter is not available here. Please consult the hardcopy thesis available from QUT Library

Bibliography

173

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