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Effects of playing surface on physiological responsesand performance variables in a controlled footballsimulationMichael G. Hughes a , Laurence Birdsey a , Rob Meyers a , Daniel Newcombe b , Jon LeeOliver a , Paul M. Smith a , Michael Stembridge a , Keeron Stone a & David George Kerwin aa Cardiff Metropolitan University, Cardiff School of Sport , Cardiff , United Kingdomb Oxford Brookes University, Sport & Health Sciences , Oxford , United KingdomPublished online: 15 Jan 2013.

To cite this article: Michael G. Hughes , Laurence Birdsey , Rob Meyers , Daniel Newcombe , Jon Lee Oliver , Paul M.Smith , Michael Stembridge , Keeron Stone & David George Kerwin (2013) Effects of playing surface on physiologicalresponses and performance variables in a controlled football simulation, Journal of Sports Sciences, 31:8, 878-886, DOI:10.1080/02640414.2012.757340

To link to this article: http://dx.doi.org/10.1080/02640414.2012.757340

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Effects of playing surface on physiological responses and performancevariables in a controlled football simulation

MICHAEL G. HUGHES1, LAURENCE BIRDSEY1, ROB MEYERS1, DANIEL NEWCOMBE2,

JON LEE OLIVER1, PAUL M. SMITH1, MICHAEL STEMBRIDGE1, KEERON STONE1, &

DAVID GEORGE KERWIN1

1Cardiff Metropolitan University, Cardiff School of Sport, Cardiff, United Kingdom, and 2Oxford Brookes University, Sport

& Health Sciences, Oxford, United Kingdom

(Accepted 6 December 2012)

AbstractIn spite of the increased acceptance of artificial turf in football, few studies have investigated if matches are altered by the typeof surface used and no research has compared physiological responses to football activity on artificial and natural surfaces. Inthe present study, participants performed a football match simulation on high-quality artificial and natural surfaces. Neithermean heart rate (171+ 9 beats �min71 vs. 171+ 9 beats �min71; P4 0.05) nor blood lactate (4.8+ 1.6 mM vs.5.3+ 1.8 mM; P4 0.05) differed between the artificial and natural surface, respectively. Measures of sprint, jumping andagility performance declined through the match simulation but surface type did not affect the decrease in performance. Forexample, the fatigue index of repeated sprints did not differ (P4 0.05) between the artificial, (6.9+ 2.1%) and naturalsurface (7.4+ 2.4%). The ability to turn after sprinting was affected by surface type but this difference was dependent on thetype of turn. Although there were small differences in the ability to perform certain movements between artificial and naturalsurfaces, the results suggest that fatigue and physiological responses to football activity do not differ markedly betweensurface-type using the high-quality pitches of the present study.

Keywords: soccer exercise, sprints, agility, fatigue, pitch-types

Introduction

Association football has traditionally been played on

grass surfaces, although the inherent variability of

such natural turf surfaces along with recent improve-

ments in artificial turf systems have led to an

increased prevalence and acceptance of third-

generation artificial surfaces (Fuller, Dick, Corlette,

& Schmalz, 2007; Soligard, Bahr, & Anderson,

2012). These surfaces are termed ‘football turf’ by

the Federation Internationale de Football Association

(FIFA; FIFA, 2009) and comprise synthetic grass

fibres laid in sand and rubber, supported by a layer of

carpet on a rigid base. Governing bodies in the sport

now increasingly support the use of football turf for

matches (FIFA, 2010a) provided these surfaces meet

a series of standardised quality-control tests (FIFA,

2009). Professional matches of the highest standard

(e.g., UEFA (Union of European Football Associa-

tions) Champion’s League and many European

domestic leagues) regularly take place on football

turf surfaces and in Europe alone, over 370 grounds

use the highest-rated ‘FIFA 2 star’ pitches (FIFA,

2012). However, few research studies have investi-

gated the effect of surface type on characteristics of

the sport although some players perceive matches on

football turf to be ‘physically harder’ than on natural

turf (Andersson, Ekblom, & Krustrup, 2008).

Playing surface is known to influence certain

components of football play. For example: accuracy

and kinematics of shooting (Potthast & Bruggemann,

2010); site of injury (Ekstrand, Hagglund, & Fuller,

2011; Ekstrand, Timpka, & Hagglund, 2006; Soli-

gard et al., 2012); passing strategy (Andersson et al.,

2008; FIFA, 2010b); slide-tackle frequency (Anders-

son et al., 2008; FIFA, 2010b) and the perception of

fatigue (Andersson et al., 2008) have all been shown

to differ between natural and artificial surfaces. In

contrast, assessment of activity profiles (distance

covered at a range of intensities) (Andersson et al.,

2008), injury prevalence (Ekstrand et al., 2011; Fuller

et al., 2007; Soligard et al., 2012) and technical

Correspondence: Michael G. Hughes, Cardiff Metropolitan University, Cardiff School of Sport, Cardiff, United Kingdom.

E-mail: mghughes@cardiffmet.ac.uk

Journal of Sports Sciences, 2013

© 2013 Taylor & Francis

Vol. 31, No. 8, 878–886, http://dx.doi.org/10.1080/02640414.2012.757340

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measures of performance (FIFA, 2010b) seem

unaffected by surface type. Given that the male

players in the study by Andersson et al. (2008)

reported that play on football turf was harder, while

the playing surface did not affect their activity profile,

it is important to consider whether surface can

influence physiological responses to football activity.

Physiological responses to constant-speed running on

artificial and natural turfs are either similar (Sassi

et al., 2011) or greater (DiMichele, DiRenzo,

Ammazzalorso, & Merni, 2009) than those on the

artificial surface, with speculation that the contrasting

cushioning properties of the surfaces influence

players’ responses (DiMichele et al., 2009). How-

ever, measurements in these studies were made

during steady-state running so their findings could

have limited application to football where there are

frequent accelerations and directional changes

(Bloomfield, Polman, & O’Donoghue, 2007a; Car-

ling, Bloomfield, Nelsen, & Reilly, 2008) that are

known to increase the demands of football play

(Dellal et al., 2010; Reilly, 1997).

General physiological responses to football match

play have been well characterised (Bangsbo, 1994;

Mohr, Krustrup, & Bangsbo, 2003; Rebelo, Krustrup,

Soares, & Bangsbo, 1998). It is typical for match play

to elicit fatigue, as evidenced by reduced distances

covered and by impaired sprint performance towards

the end of matches and immediately after periods of

high-intensity exercise (Carling & Dupont, 2011;

Mohr, Krustrup, & Bangsbo, 2005; Rebelo et al.,

1998). An appreciation of the physiological responses

is especially important given that fatigue is associated

with increased risk of injury (Greig & Siegler, 2009;

Woods et al., 2004) and a decline in skilled perfor-

mance (Russell, Benton, & Kingsley, 2011; Stone &

Oliver, 2009). However, match activities in football

are highly variable (Bangsbo, 1994) so several proto-

cols have been developed in an attempt to simulate

responses to football play with improved control

(Drust, Reilly, & Cable, 2000; Nicholas, Nuttall, &

Williams, 2000; Stone et al., 2011). A criticism of

perhaps the most widely used of these protocols (the

‘Loughborough Intermittent Shuttle Test – LIST’

protocol; Nicholas et al., 2000) is that it can under-

estimate the physiological stresses of match play

(Drust, Atkinson, & Reilly, 2007; Magalhaes et al.,

2010) and it fails to include the high-speed turns and

intermittent periods of repeated sprints that charac-

terise match play (Bloomfield, Polman, & O’Dono-

ghue, 2007b; Bradley et al., 2009). An adaptation of

the LIST protocol has recently been presented that

simulates the demands of football match play and

overcomes these shortcomings (Soccer Simulation

Protocol; Stone et al., 2011).

No studies have investigated the effects of surface-

type on the combination of physiological and fatigue

responses to football activity. Andersson et al. (2008)

specifically highlighted the need for such a study to

be conducted during match-play however this might

be an inappropriate approach given the variability of

matches (Drust et al., 2007; Russell & Kingsley,

2011). The desire to maintain the characteristics of

matches in the face of increased use of football turf

surfaces means that objective studies are needed to

address if physiological responses in football are

altered by playing surface. Therefore, the aim of the

present study was to investigate the effect of playing

surface using a protocol that simulates the physiolo-

gical demands of football activity. Because of the

performance measures inherent in the present study,

a secondary aim was to investigate effects of playing

surface on sprinting and agility performance.

Methods

Participants

Seventeen semi-professional outfield football players

participated. The mean characteristics of the players

were age 22.8+ 2.1 years, stature 1.79+ 0.05 m and

body mass 76.3+ 5.7 kg. The institutional ethics

committee approved the project and written informed

consent was obtained from all players. Players were

accepted onto the study only after successfully

completing a full medical examination, according to

the standards of England’s ‘Football Association’.

Overview of experimental design

After habituation, participants performed two sepa-

rate trials of the soccer-simulation protocol on high-

quality football turf and natural turf surfaces. The

two pitches were located within 10 km of each other

to ensure similar climatic conditions for the con-

current trials. Participants were randomly assigned to

groups and tested in groups of four or five with one

trial on each surface being held concurrently. Test

sessions were separated by 72 h both to ensure

recovery between trials and to minimise diurnal

variation in performance. Immediately before and

after each simulation trial, participants performed

tests of agility, sprint speed and vertical jump height.

Conditions were dry on both test days and the mean

(s) air temperature was 27.5 (2.1) 8C during testing.

Preparation for test administration

To ensure that the natural turf surface was of the

highest quality, independent experts in turf prepara-

tion made preliminary visits to a range of sites in the

two months before testing. After identification of

suitable locations, checks of quality control were

made before a final location was established whose

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characteristics were verified as being of the highest

quality for grass pitches according to the criteria

given in Baker (1999) and Baker, Spring, and

Wheater (2007). The artificial surface met the

criteria of a ‘FIFA 2 star’ pitch, which is FIFA’s

highest rating for football turf (FIFA, 2009).

Participants were prepared for the test sessions by

attending a separate practice session in which they

were habituated to the procedures by completing one

16-min block of the simulation protocol. Prior to the

simulation trial, participants completed a standar-

dised warm-up including jogging at a controlled

speed for five minutes, four minutes of dynamic

stretching and three 15-m sprints in two minutes.

Participants then performed the ‘pre-post’ tests

described below. The players wore identical football

boots (Copa Mundial, Adidas, Germany) and foot-

ball clothing (Adidas, Germany) during all testing.

Participants were accommodated in a training camp

during the experiment so their nutrition, volume of

additional exercise and timings for meals were

similar throughout the duration of the study.

‘Pre-post’ performance measures

To quantify the extent to which performance was

affected, tests were performed before and after the

soccer-simulation protocol in the following order:

‘L-agility’ run, 60 m sprints and vertical jump height.

Agility was assessed using the ‘L-agility’ run (Webb &

Lander, 1983) whereby participants sprinted forward

5 m, turned 908, sprinted 5 m, turned 1808, sprinted

5 m, turned 908 and sprinted 5 m back to the start/

finish line. Participants completed two trials, one with

an initial turn to the left and one with a turn to the

right, with the mean of these trials used for analysis.

Participants completed two trials of a 60-m straight

sprint, with the better performance used for subse-

quent data analysis. The L-agility and sprint times were

measured using timing gates (SmartSpeed, Fusion

Sport, Brisbane, Australia) on the same pitch as the

corresponding simulation trial. Participants then com-

pleted two trials of a countermovement vertical jump

test (SmartJump, Fusion Sport, Brisbane, Australia)

on a nearby concrete surface, with the better effort used

for subsequent analysis. Between two and three

minutes of recovery were given between trials in all

performance tests. Within three minutes of completing

the jump test, participants began the simulation

protocol. Within three minutes of completing the

entire soccer simulation, participants performed the

same ‘pre-post’ tests in the same order.

The soccer-simulation protocol (SSP)

The soccer simulation (Stone et al., 2011) required

participants to complete six 16-minute ‘sets’ of

simulated football activity with a three-minute rest

between sets and a 15-minute half-time break. The

procedure required participants to complete inter-

mittent shuttle runs at speeds representing walking,

jogging, running and all-out sprinting efforts. Within

the procedure, participants also completed one bout

of repeated sprints in each set and a sprint-agility

run. The procedure was organised as repeated cycles

of exercise, structured as follows:

. 36 20 m at a walking pace of 1.43 m � s71

. 16 sprint-agility run at maximal intensity (20 s

for sprint and recovery)

. 36 20 m at a jogging speed of 2.5 m � s71

. 36 20 m at a running speed of 4.0 m � s71

Each cycle of activity lasted for 107 s and was

performed a total of eight times during each set.

Midway through each set players were required to

complete a series of six 15-m repeated sprints,

starting every 18 s. The total distance covered during

the whole simulation was approximately 11.2 km. A

schematic of the test layout is shown in Figure 1.

Participants completed walking, jogging and running

in a 20-m lane marked out by cones (lane A) and a

separate lane was placed adjacent to this to measure

the sprint-agility run and repeated sprint perfor-

mance (lane B) using timing gates (SmartSpeed,

Fusion Sports, Brisbane, Australia). The sprint-

agility run and repeated sprint bouts commenced

from a standing start behind the first timing gate.

Instructions and activity speeds were provided

throughout the protocol using a pre-recorded audio

track. The sprint-agility run provided three measures

of performance: the time taken to cover the initial

straight 15 m (‘sprint-agility run 15m’; points 1-2 in

Figure 1. Schematic of the layout for the soccer simulation

protocol. Lane A was used for the walking, jogging and running at

controlled intensities. Lane B was used for repeated sprints and

the sprint-agility run. The order of the sprint-agility run was as

numbered (1-2-3-2-1) in the direction of the arrows. (Filled circles

are timing gates, open circles are marker cones).

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Figure 1), the time to cover the subsequent 10 m that

included a 1808 turn (‘sprint-agility run turn’; points

2-3-2) and the time to cover the final 17 m section

which included a 738 change of direction midway

through the sprint (‘sprint-agility run cut’; points 2-

1). Reproducibility of performance measures like

those used here is typically very good with coeffi-

cients of variations less than 5% (Buchheit, Spencer,

& Ahmaidi, 2010; Glaister et al., 2007; Oliver &

Meyers, 2009).

Throughout the protocol participants were al-

lowed to drink water and a 4% CHO beverage ad

libitum. Heart rate (HR) was monitored using Polar

s610 heart rate monitors (Polar Electro, Finland)

and mean HR was calculated for each set of the SSP

and the highest 5-s reading for each set was taken as

the peak HR for that set. Blood lactate concentration

was analysed from capillary samples following each

set of the SSP using a Biosen C-Line lactate analyser

(EFK Diagnostics, Barleben, Germany).

Data analysis

Data analyses were completed using SPSS (version

17, SPSS, Chicago, USA), with statistical signifi-

cance accepted at P5 0.05. Unless otherwise stated,

all data were analysed using separate fully repeated

measures factorial analysis of variance (ANOVA)

tests. A 26 2 model examined L-agility, 60-m sprint

and vertical jump performance (surface6 pre-post).

A 26 6 model examined variables recorded during

or after each set of the simulation protocol (sur-

face6 set), which included: blood lactate concentra-

tion at the end of each set, peak HR and mean values

for all of the other variables within each set (i.e., HR

and performance times for the repeated sprints and

the three components of the sprint-agility run). A

fatigue index (percentage decrement; Glaister,

Stone, Stewart, Hughes, & Moir, 2004) was

calculated from the repeated sprint test times.

When assumptions of sphericity were violated, the

Huynh-Feldt adjustment was applied. Significant

main effects were further explored using a Bonfer-

onni post hoc adjustment. Paired t-tests compared the

fatigue index and the best single (i.e., ‘peak’) times

for each participant in the repeated sprint bouts and

in each component of the sprint-agility runs (i.e., 15-

m sprint, turn and cut). To identify meaningful

changes in the performance tests, 90% confidence

intervals and effect sizes (ES; Cohen’s d) were also

calculated (Hopkins, 2003). The threshold values for

ES ratings were 0.2 and 0.5 for small and moderate

effects, respectively (Thomas, Salazar, & Landers,

1991). All data are presented as mean+ s unless

stated otherwise.

Results

Physiological responses to the soccer simulation protocol

There were no differences (P4 0.05) between

playing surfaces in the physiological responses to

the soccer simulation protocol (Table I). There were

main effects for set number such that blood lactate

concentration was lower towards the end of the

protocol, while both mean and peak HR responses

were lower in the early stages of the protocol. There

were no interactions between playing surface and set

number in the simulation for these physiological

variables.

Performance measures

‘Pre-post’ performance measures. Mean pre-post data

for both playing surfaces are displayed in Table II.

The analysis of the pre-post main effects showed a

decline in performance after the simulation for the

Table I. Physiological responses to the soccer simulation protocol on artificial (‘football turf’) and natural turf.

Blood lactate (mM) Mean HR (beats �min-1) Peak HR (beats � min-1)

Football

turf

Natural

turf

Mean

across

set number

Football

turf

Natural

turf

Mean

across

set number

Football

turf

Natural

turf

Mean

across

set number

Set 1 5.6 + 1.6 6.0 + 1.9 5.8 + 1.7 168 + 9 170 + 8 169 + 9*2,3 180 + 7 182 + 8 181 + 8*2,3

Set 2 5.3 + 2.1 5.9 + 1.9 5.6 + 2.0 172 + 8 173 + 9 172 + 8 183 + 8 184 + 9 183 + 9

Set 3 5.6 + 1.8 5.6 + 1.9 5.6 + 1.8 172 + 9 174 + 10 173 + 9 184 + 9 183 + 9 184 + 9

Set 4 4.7 + 1.4 4.8 + 1.8 4.7 + 1.5*1 168 + 10 167 + 9 168 + 9*2,3,5,6 182 + 10 181 + 9 181 + 9*5

Set 5 4.1 + 1.2 4.9 + 1.5 4.5 + 1.4*1,2,3 172 + 9 171 + 10 172 + 9 183 + 8 183 + 9 183 + 8

Set 6 3.9 + 0.9 4.7 + 1.8 4.3 + 1.5*1,2,3 173 + 8 172 + 9 172 + 9 184 + 9 182 + 9 183 + 9

Mean across

surface type

4.8 + 1.6 5.3 + 1.8 171 + 9 171 + 9 182 + 9 182 + 9

Values are mean + s.

*Lower result than in sets indicated (P 5 0.05).

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L-agility run, the 60-m sprint and the vertical jump

height data. There was no main effect of playing

surface for 60-m sprint performance (P4 0.05;

ES¼ 0.08), but for the L-agility test, there was a

main effect for playing surface, such that test

performance was slower on natural turf than on

football turf (P5 0.05; ES¼ 0.42). However, the

absence of interactions (surface6 pre-post) for any

of these variables indicates that playing surface did

not have an additional effect on the development of

fatigue.

Performance measures in the soccer-simulation protocol.

The 15-m sprint performances within the sprint-

agility run (see Table III) and in the repeated sprint

bouts (Figure 2) were similar. In both cases, there

was a (P5 0.05) decline in sprint performance with

mean times in set 1 being shorter than sets 3, 4, 5

and 6 and with set 2 being shorter than set 6.

Additionally, mean repeated sprint time for set 1 was

faster than set 2 (P5 0.05). There was no main

effect of playing surface and no interaction (sur-

face6 set) for 15-m sprint performances in either the

repeated sprints or the sprint-agility runs. The

fatigue index for repeated sprint times was not

different between natural and football turfs

(6.9+ 2.1% vs. 7.4+ 2.4%, respectively;

P4 0.05). For the ‘turns’ within the sprint-agility

run there was a main effect of set number showing a

deterioration in performance through the trial

(P5 0.05). There was also a main effect of surface

showing that this movement was performed more

quickly on natural, compared to football turf

(P5 0.05; ES¼ 0.45 for comparison of mean data)

and an interaction (surface6 set) specifically show-

ing faster turns on natural turf for sets 1, 3, 5 and 6

(Figure 3; P5 0.05). There were no differences for

any main effect when ‘cuts’ from the sprint-agility

runs were analysed (Table III).

Comparison of peak performance between playing sur-

face. The results of the fastest efforts for each

Table II. Agility, 60-m sprint time and vertical jump results taken before and after (i.e., pre & post) the soccer simulation protocol performed

on artificial (‘football turf’) and natural turf.

Mean performance (+s)

Comparison of pre-post difference

scores for test surface

Variable Surface Pre Post

Mean for test

surface

Mean difference

(90% CI)

Effect

size

L-agility time (s) Football turf 5.08 + 0.15 5.13 + 0.17 5.11 + 0.16*b

0.36Natural turf 5.11 + 0.17 5.22 + 0.14 5.17 + 0.16 0.05s (70.04 to 0.13 s)

Mean for pre and post 5.10 + 0.16*a 5.18 + 0.16

60 m sprint time (s) Football turf 7.90 + 0.39 8.04 + 0.43 7.97 + 0.41

0.14Natural turf 7.94 + 0.39 8.05 + 0.45 8.00 + 0.44 0.03s (70.09 to 0.15 s)

Mean for pre and post 7.92 + 0.38*a 8.04 + 0.44

Vertical jump (cm) Football turf 29.8 + 3.6 27.5 + 2.9 28.6 + 3.4

0.12Natural turf 29.8 + 2.7 27.9 + 3.8 28.8 + 3.4 70.3cm (72.2 to 1.5 cm)

Mean for pre and post 29.8 + 3.1*a 27.7 + 3.3

*aDifference between pre and post values (P 5 0.05).

*bDifference between playing surface (P 5 0.05).

CI – confidence interval.

Table III. Mean times for 15 m sprint and ‘cut’ components of the

sprint-agility run (S-AR) performed on artificial (‘football turf’)

and natural turf in the six sets of the soccer simulation protocol.

S-AR 15m sprint time (s) S-AR cut time (s)

Football turf Natural turf Football turf Natural turf

Set 1 2.60 + 0.11 2.59 + 0.08 2.89 + 0.12 2.87 + 0.14

Set 2 2.59 + 0.13 2.63 + 0.1 2.88 + 0.12 2.92 + 0.14

Set 3 2.63 + 0.12 2.64 + 0.10 2.91 + 0.19 2.94 + 0.15

Set 4 2.63 + 0.14 2.71 + 0.11 2.93 + 0.20 2.95 + 0.13

Set 5 2.65 + 0.16 2.67 + 0.11 2.91 + 0.19 2.92 + 0.14

Set 6 2.64 + 0.15 2.70 + 0.13 2.94 + 0.16 2.97 + 0.18

Values are mean + s.

Figure 2. Mean times for the 15-m repeated sprints on football turf

(FT) and natural turf (NT) in the soccer simulation protocol.

Values are mean+ s, HT- half-time. # Set 1 faster than all other

sets (main effect of set; P5 0.05). } Set 2 faster than set 6 (main

effect of set; P50.05).

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component of the simulation are given in Table IV.

The peak 15-m sprint performances (i.e., from the

sprint-agility run and the repeated sprint bouts) were

faster on football turf (ES¼ 0.39 and 0.35, respec-

tively; both P5 0.05). From the sprint-agility runs,

the peak turn results were faster on the natural turf

(P5 0.05; ES¼ 0.49) while the peak cut data were

not different according to playing surface (P4 0.05;

ES¼ 0.23).

Discussion

The present study shows that physiological responses

to simulated soccer activity do not differ between the

high-quality natural and artificial pitches used in the

present study. The performance tests, however, show

that playing surface has a small influence on maximal

speed of movement during sprinting and turning

activities.

Responses to the protocol in this study further

confirm that it was an effective simulation of soccer

match play. This is demonstrated both by the

physiological responses and the fact that fatigue

occurred in many performance measures through the

protocol. The HR and blood lactate responses to the

simulation were consistent with well-established data

from soccer matches (Bangsbo, 1994; Bangsbo, Iaia,

& Krustrup, 2007; Mohr et al., 2005; Reilly, 1997).

The decline in maximal performance for turning and

sprinting seen with the simulation is further evidence

of the suitability of this procedure; similar findings

have been observed both during (Bradley et al.,

2009; Mohr et al., 2003) and after match play

(Krustrup, Zebis, Jensen, & Mohr, 2010; Mohr

et al., 2003; Rebelo et al., 1998) where similar

performance measures have been used. Although the

simulation did not involve activity with a football this

is unlikely to influence the impact of our findings as

less than 2% of a match is spent in possession of the

ball (Bangsbo, 1994; Reilly, 1997). Additionally, in

relation to the specific aims of this study, male

players in the work by Andersson et al. (2008)

perceived that running off-the-ball was harder on

football turf, compared to natural. Therefore, this

protocol should allow identification of differences in

physiological responses and fatigue between the two

playing surfaces.

Although previous research has investigated effects

of playing surface on physiological responses to

steady-speed running (DiMichele et al., 2009; Sassi

et al., 2011), no research has explored these

responses during football activity. The data from

the present study demonstrate no differences in

blood lactate concentration and HR responses to the

simulation. Similarly, by using a range of perfor-

mance measures, the extent of fatigue experienced by

the players during the protocol can be evaluated.

Declines in performance due to the procedure

occurred in the tests of straight-line sprinting,

turning and jumping but once again, there was no

evidence that playing surface had an additional role

in the development of fatigue.

The male participants in the study of Andersson

et al. (2008) reported that football was ‘physically

harder’ on artificial, compared to natural turf and the

present study used a combination of performance

measures and physiological responses to investigate if

the use of football turf influences the tolerance to

perform football activities. That neither the physio-

logical responses nor the performance tests differed

Table IV. Peak performance times for sprint and agility movements in the soccer simulation protocol on artificial (‘football turf’) and natural

turf.

Variable Football turf Natural turf Mean difference (90% CI)(s) Effect size

RS 15-m sprint time (s) 2.51 + 0.12* 2.55 + 0.10 0.04 (0.01 to 0.07) 0.35

S-AR 15-m sprint time (s) 2.45 + 0.13* 2.49 + 0.08 0.05 (0.02 to 0.08) 0.39

S-AR turn time (s) 2.59 + 0.09* 2.55 + 0.07 0.04 (0.02 to 0.06) 0.49

S-AR cut time (s) 2.70 + 0.11 2.74 + 0.10 0.03 (0.01 to 0.06) 0.23

*Difference between playing surface (P 5 0.05).

RS – repeated sprint, S-AR – Sprint agility run, CI – confidence interval.

Figure 3. Mean times for the turn component of the sprint-agility

run (S-AR) on football turf (FT) and natural turf (NT) in the

soccer simulation protocol. Values are mean+ s, HT- half-time.

*For sets 1, 3, 5, and 6 turns were faster on natural turf

(surface6 set interaction; P5 0.05). # Set 6 slower than sets 1, 2,

and 5 (main effect of set; P5 0.05).

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in the extent of fatigue between surfaces provides

objective evidence that, for the high-quality playing

surfaces used in the present study, physiological

demands of the soccer simulation were similar

between surfaces. The possibility remains, however,

that psychological factors contributed to the higher

values of perceived exertion on football turf. Some

participants reported that turning on the natural turf

was easier, but others held the opposite view. In

terms of the overall exertion perceived, participants

generally reported no difference between surfaces.

Further research is recommended to extend the

assessment of performance times used here to see if

movement technique differs between surfaces.

The variety of measures used in the present study

allows a thorough comparison of the effects of the

surfaces. These results could be helpful in explaining

why some players show differences in effort percep-

tion due to surface type. Our results suggest that

small differences in performance characteristics

occur especially where changes of direction are

required. Specifically, this observation is supported

by L-agility test data and the ‘turn’ component of the

sprint-agility run. For the L-agility test, two 90-

degree directional changes were interspersed by a

180-degree turn performed with one foot planted to

make the turn and this test was performed faster on

football turf. The turn in the sprint-agility run was

also 180-degrees but occurred at the end of a 20-m

sprint around a cone 0.28 m in diameter, so these

turns were made with many small steps and the

overall performance times for this activity were

slower on football turf. The difference in the ‘turn’

results occurred both for the mean and peak

performances through the protocol, suggesting that

it was a general characteristic between the two

surfaces and not one that could be attributed to

fatigue or wear on the pitch. Thus, although changes

of direction are affected by playing surface, effects on

performance seem to be dependent on the type of

manoeuvre. Effect sizes (all below 0.5, therefore

rated as being no more than ‘small effects’; Hopkins,

Marshall, Batterham, & Hanin, 2009; Thomas et al.,

1991) confirm the low magnitude of these differ-

ences, but the range of 90% CI for the peak

performance data excludes zero, supporting the

notion that small, but meaningful differences occur

for these movements between surfaces. For the

straight-line sprints, there were trends for 15-m and

60-m performance to be better on football turf, but

this difference was only statistically significant when

the ‘peak performance’ 15-m sprint data were

compared (Table IV). There were no differences in

performance for the ‘cut’ movement from the sprint-

agility run. Previous research has highlighted that

turning movements elicit different biomechanical

responses on artificial, compared to natural surfaces

(Ford et al., 2006; Villwock, Meyer, Powell, Fouty,

& Haut, 2009) so further work should be directed

towards establishing how playing surface influences

directional changes. Modern artificial turf systems

are clearly similar to natural turf for many of the

responses in this study but these findings suggest that

there are small differences for certain turning move-

ments and that manufacturers should focus on this

aspect of the player-surface interface to improve

replication of natural surfaces.

It is important to highlight that this study used

high-quality pitches for both playing surfaces.

Although authorities in the sport have strict guide-

lines for the quality of football turf, there are no such

standards for natural surfaces (FIFA, 2010a). As a

consequence, findings of the present study should

not be generalised to lower-quality surfaces and

further research should address the variability across

a range of natural surfaces before definitive conclu-

sions can be made on the effect of playing surface on

physiological demands of the sport.

In summary, the present study is the first to make a

controlled comparison of fatigue and physiological

responses to football activity on natural turf and

‘football turf’. Using high-quality natural and artifi-

cial surfaces and a controlled football simulation,

neither the physiological responses nor the extent of

fatigue differed according to surface.

Acknowledgements

The authors wish to acknowledge FIFA who funded

the study as part of a larger research project,

coordinated by Stuart Larman and Professor Len

Nokes, both of FIFA. The authors would also like to

thank the Sports Turf Research Institute and Fusion

Sport Ltd for their technical support in this study.

References

Andersson, H., Ekblom, B., & Krustrup, P. (2008). Elite football

on artificial turf versus natural grass: Movement patterns,

technical standards, and player impressions. Journal of Sports

Sciences, 26, 113–122.

Baker, S. W. (1999). The playing quality of turfgrass sports

surfaces. In D. E. Aldous (Ed.), The International Turf

Management Handbook (pp. 231–244). Oxford: Butterworth-

Heinemann.

Baker, S. W., Spring, C. A., & Wheater, J. A. (2007). Performance

requirements for surface hardness of winter pitches. Journal of

Turfgrass and Sports Surface Science, 83, 91–97.

Bangsbo, J. (1994). The physiology of soccer with special

reference to intense intermittent exercise. Acta Physiologica

Scandinavica, 15(159 Suppl. 1), 1–155.

Bangsbo, J., Iaia, F. M., & Krustrup, P. (2007). Metabolic

response and fatigue in soccer. International Journal of Sports

Physiology and Performance, 2, 111–127.

Bloomfield, J., Polman, R., & O’Donoghue, P. (2007a). Decel-

eration movements performed during FA Premier League

soccer matches. Journal of Sports Science and Medicine, 6(Suppl.

10), 6.

884 M. G. Hughes et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 0

9:43

05

Janu

ary

2014

Bloomfield, J., Polman, R., & O’Donoghue, P. (2007b). Turning

movements performed during FA Premier League soccer

matches. Journal of Sports Science and Medicine, 6(Suppl. 10),

9–10.

Bradley, P. S., Sheldon, W., Wooster, B., Olsen, P., Boanas, P., &

Krustrup, P. (2009). High-intensity running in English FA

Premier League soccer matches. Journal of Sports Sciences, 27,

159–168.

Buchheit, M., Spencer, M., & Ahmaidi, S. (2010). Reliability,

usefulness and validity of a repeated sprint and jump ability test.

International Journal of Sports Physiology and Performance, 5,

3–17.

Carling, C., Bloomfield, J., Nelsen, L., & Reilly, T. (2008). The

role of motion analysis in elite soccer. Sports Medicine, 38,

839–862.

Carling, C., & Dupont, G. (2011). Are declines in physical per-

formance associated with a reduction in skill-related perfor-

mance during professional soccer match play? Journal of Sports

Sciences, 29, 63–71.

Dellal, A., Keller, D., Carling, C., Chaouachi, A., Wong, D. P., &

Chamari, K. (2010). Physiologic effects of directional changes

in intermittent exercise in soccer players. Journal of Strength and

Conditioning Research, 24, 3219–3226.

DiMichele, R., DiRenzo, A. M., Ammazzalorso, S., & Merni, F.

(2009). Comparison of physiological responses to an incre-

mental running test on treadmill natural grass, and synthetic

turf in young soccer players. Journal of Strength and Conditioning

Research, 23, 939–945.

Drust, B., Atkinson, G., & Reilly, T. (2007). Future perspectives

in the evaluation of the physiological demands of soccer. Sports

Medicine, 37, 783–805.

Drust, B., Reilly, T., & Cable, N. T. (2000). Physiological

responses to laboratory-based soccer-specific intermittent and

continuous exercise. Journal of Sports Sciences, 18, 885–892.

Ekstrand, J., Hagglund, M., & Fuller, C. W. (2011). Comparison

of injuries sustained on artificial turf and grass by male and

female elite football players. Scandinavian Journal of Medicine

and Science in Sports, 21, 824–832.

Ekstrand, J., Timpka, T., & Hagglund, M. (2006). Risk of injury

in elite football played on artificial turf versus natural grass: A

prospective two-cohort study. British Journal of Sports Medicine,

40, 975–980.

Federation Internationale de Football Association (FIFA). (2009).

FIFA quality concept for football turf. Retrieved from http://

www.fifa.com/aboutfifa/developing/pitchequipment/footballturf

/fqc.html

Federation Internationale de Football Association (FIFA).

(2010a). Laws of the game 2010–2011. Retrieved from http://

www.fifa.com/aboutfifa/documentlibrary/doclists/laws.html#

laws

Federation Internationale de Football Association (FIFA).

(2010b). Technical study 4: Turf Roots magazine, 37–42.

Retrieved from http://www.fifa.com/mm/document/afdevelop

ing/pitchequip/turfrootsmagazine_02_37450.pdf

Federation Internationale de Football Association (FIFA). (2012).

FIFA recommended pitches worldwide. Retrieved from

http://www.fifa.com/aboutfifa/organisation/marketing/quality

programme/footballturf/pitchesproducts/index.html

Ford, K. R., Manson, N. A., Evans, B. J., Myer, G. D., Gwin, R.

C., Heidt, R. S., & Hewett, T. E. (2006). Comparison of in-

shoe foot loading patterns on natural grass and synthetic turf.

Journal of Science and Medicine in Sport, 9, 433–440.

Fuller, C. W., Dick, R. W., Corlette, J., & Schmalz, R. (2007).

Comparison of the incidence, nature and cause of injuries

sustained on grass and new generation artificial turf by male

and female football players. Part 1: match injuries. British

Journal of Sports Medicine, 41(Suppl. 1), i20–i26.

Glaister, M., Howatson, G., Lockey, R. A., Abraham, C. S.,

Goodwin, J., & McInnes, G. (2007). Familiarization and

reliability of multiple sprint running performance indices.

Journal of Strength and Conditioning Research, 21, 857–859.

Glaister, M., Stone, M. H., Stewart, A. M., Hughes, M., & Moir,

G. L. (2004). The reliability and validity of fatigue measures

during short-duration maximal intermittent cycling. Journal of

Strength and Conditioning Research, 18, 459–462.

Greig, M., & Siegler, J. C. (2009). Soccer-specific fatigue and

eccentric hamstrings muscle strength. Journal of Athletic

Training, 44, 180–184.

Hopkins, W. G. (2003). How to analyze a straightforward cross-

over trial [Excel spreadsheet]. Retrieved from http://www.

newstats.org/xcrossover.xls

Hopkins, W. G., Marshall, S. W., Batterham, A. M., & Hanin, J.

(2009). Progressive statistics for studies in sports medicine and

exercise science. Medicine and Science in Sports and Exercise, 41,

3–12.

Krustrup, P., Zebis, M., Jensen, J. M., & Mohr, M. (2010).

Game-induced fatigue patterns in elite female soccer. Journal of

Strength and Conditioning Research, 24, 437–441.

Magalhaes, J., Rebelo, A., Oliveira, E., Silva, J. R., Marques, F., &

Ascensao, A. (2010). Impact of Loughborough intermittent

shuttle test versus soccer match on physiological, biochemical

and neuromuscular parameters. European Journal of Applied

Physiology, 108, 39–48.

Mohr, M., Krustrup, P., & Bangsbo, J. (2003). Match perfor-

mance of high-standard soccer players with special reference

to development of fatigue. Journal of Sports Sciences, 21,

519–528.

Mohr, M., Krustrup, P., & Bangsbo, J. (2005). Fatigue in soccer:

A brief review. Journal of Sports Sciences, 23, 593–599.

Nicholas, C. W., Nuttall, F. E., & Williams, C. (2000). The

Loughborough intermittent shuttle test: A field test that

simulates the activity pattern of soccer. Journal of Sports Sciences,

18, 97–104.

Oliver, J., & Meyers, R. W. (2009). Reliability and generality of

measures of acceleration, planned agility and reactive agility.

International Journal of Sports Physiology and Performance, 4,

345–354.

Potthast, W., & Bruggemann, G.-P. (2010). Motion differences in

goal kicking on natural and artificial soccer turf systems.

Footwear Science, 2, 29–35.

Rebelo, N., Krustrup, P., Soares, J., & Bangsbo, J. (1998).

Reduction in intermittent exercise performance during a soccer

match. Journal of Sports Sciences, 16, 482–483.

Reilly, T. (1997). Energetics of high-intensity exercise (soccer)

with particular reference to fatigue. Journal of Sports Sciences, 15,

257–263.

Russell, M., Benton, D., & Kingsley, M. I. C. (2011). The effects

of fatigue on soccer skills performed during a soccer match

simulation. International Journal of Sports Physiology and

Performance, 6, 221–223.

Russell, M., & Kingsley, M. (2011). Influence of exercise on skill

proficiency in soccer. Sports Medicine, 41, 523–539.

Sassi, A., Stefanescu, A., Menaspa, P., Bosio, A., Riggio, M., &

Rampinini, E. (2011). The cost of running on natural grass and

artificial turf surfaces. Journal of Strength and Conditioning

Research, 25, 606–611.

Soligard, T., Bahr, R., & Andersen, T. E. (2012). Injury risk

on artificial turf and grass in youth tournament football.

Scandinavian Journal of Medicine and Science in Sports, 22,

356–361.

Stone, K., & Oliver, J. L. (2009). The effect of 45 minutes of

soccer-specific exercise on the performance of soccer skills.

International Journal of Sports Physiology and Performance, 4,

163–175.

885Physiological responses and soccer playing surface

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 0

9:43

05

Janu

ary

2014

Stone, K. J., Oliver, J. L., Hughes, M. G., Stembridge, M.,

Newcombe, D. J., & Meyers, R. W. (2011). Development of a

soccer simulation protocol to include repeated sprints and

agility. International Journal of Sports Physiology and Performance,

6, 427–431.

Thomas, J. R., Salazar, W., & Landers, D. M. (1991). What is

missing in p5 .05? Effect size. Research Quarterly for Exercise

and Sport, 62, 344–348.

Villwock, M. R., Meyer, E. G., Powell, J. W., Fouty, A., & Haut,

R. C. (2009). Football playing surface and shoe design affect

rotational rotation. American Journal of Sports Medicine, 37, 518–

525.

Webb, P., & Lander, J. (1983). An economical fitness testing

battery for high school and college rugby teams. Sports Coach, 7,

44–46.

Woods, C., Hawkins, R. D., Maltby, S., Hulse, M., Thomas, A.,

& Hodson, A. (2004). The Football Association Medical

Research Programme: An audit of injuries in professional

football-analysis of hamstring injuries. British Journal of Sports

Medicine, 38, 36–41.

886 M. G. Hughes et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f C

onne

ctic

ut]

at 0

9:43

05

Janu

ary

2014