muscle power predicts freestyle swimming performance · performance...

Br J Sp Med 1992; 26(3)

Muscle power predicts freestyle swimmingperformance

John A. Hawley MA, BSc(Hons), Maynard M. Williams MSc, Michael M. Vickovic MSc andPhillip J. Handcock MScSchool of Physiotherapy, Faculty of Health Studies, Auckland Institute of Technology, Auckland, New Zealand

The purpose of this study was to determine the relation-ship between non-invasive laboratory measures of 'musclepower' and swim performance over sprint (50m) andmiddle-distance (400 m) events. Twenty-two swimmersperformed an upper and lower body Wingate AnaerobicTest (WAT) and a maximal sustained power output test(MPO) for the upper body. Peak power (PP) and meanpower (MP) were determined for the WAT, while peaksustained workload (WLP,..d was determined for theMPO. Timed swims over 50m and 400m were undertakenby all swimmers during which the number of arm strokesper length was recorded. Highly significant relationshipswere found between sprint-swim speed (S50) and meanpower of the arms (MP.) (r = 0.63, P < 0.01), betweenS50 and mean power of the legs (MP1,.) (r = 0.76, P <0.001) and between S50 and the distance covered with eacharm stroke (DS) (r = 0.91, P < 0.001). Multiple regressionanalyses revealed that WAT power indices for the legs didnot significantly increase explained variance in S50 abovethat of the arms. The relationship between Wp,,k andS400 was highly significant (r = 0.70, P < 0.001) andindicates the importance of arm power in the longerdistance swim events.

Keywords: Anaerobic power, muscle power, performanceprediction, swimming, Wingate Test

Recently a number of studies have emphasized theimportant role of 'muscular power' as a determinantof athletic performance5. Correlations ranging from0.71 to 0.90 have been reported between measures ofshort-term (<45 s) maximal upper body power andfreestyle swimming speed69. With regard to runningand cycling it has been suggested that the primaryvariable that predicts endurance performance is thepeak workload (or speed) an athlete can achieveduring an incremental maximal test2-5.The Wingate Anaerobic Test (WAT) has been

utilized by a number of laboratories for the evaluationof short-term, high-intensity exercise7' 10-12. Thevalidity and reliability of the WAT has beendocumented previously13. With respect to the rela-

tionship between this laboratory test and swimmingperformance, Inbar and Bar-Or7 found a correlationof -0.92 between mean power of the arms (MParm.)and 25-m freestyle time in a small group (n = 9) ofyoung swimmers. Recently, Hawley and Williams1reported highly significant relationships betweenMParmS and swim speeds over 50m (r = 0.83, P <0.001) and 400m (r = 0.63, P < 0.01) for male andfemale swimmers. To date only one study hasassessed the relationship between the WAT for thelower body and swimming performance7.We were interested in examining the role of muscle

power and its relationship to swimming perform-ance. Specifically, the aims of the current study were:

1. to assess the relationship between upper andlower body anaerobic power, as assessed by theWAT, and a 50-m sprint-swim performance;

2. to determine whether a combination of arm andleg power improves prediction of sprint-swimperformance above that of arm or leg power alone;

3. to assess the relationship between the peaksustained workload (WLp,,k) attained during amaximal sustained power output test (MPO) andswim performance over 400 m.

Materials and methodsSubjects and trainingTwelve male and ten female swimmers participatedin this investigation after giving informed consent inaccordance with the guidelines outlined by theAmerican College of Sports Medicine'4. Swimmerswere familiar with both physiological and anthro-pometric testing procedures, having served as sub-jects in several previous studies"' 1516. Subjects hadbeen training daily for the 3 months before this study,swimming on average 5000mday', 6 days a week.None of the subjects had participated in any formalstrength-training programme for 6 months beforeinvestigation.

Address for correspondence: John A. Hawley, Liberty Life Chair ofExercise and Sports Science and MRC/UCT Bioenergetics ofExercise Research Unit, Department of Physiology, University ofCape Town Medical School, Observatory 7925, South Africa

©) 1992 Butterworth-Heinemann Ltd0306-3674/92/030151-05

Physiological testingTesting was undertaken over a 7-day period duringthe swimmers' competitive season. A mechanicallybraked Monark 818E cycle ergometer (Monark,Stockholm, Sweden), interfaced with an Apple HIE

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Muscle power and swimming performance: J. A. Hawley et al.

microcomputer, (Apple, Chicago, Illinois, USA) wasemployed for the lower body WAT. The warm-upprotocol and determination of power outputs fromthe WAT have been described previously'2" 3. Theforces chosen for the lower body WAT were0.070kgkg-1 body mass for males and 0.067kgkg-1body mass for females'7. For upper body testing aMonark 881E ergometer (Monark, Stockholm,Sweden) was interfaced with a microcomputer.Calculation of WAT indices for the upper body testand the warm-up protocol employed have beendescribed elsew ere. Forces for the upper bodyWAT were 0.037kg kg-' body mass and 0.029 kg kg-'body mass for males and females respectively' . TheWAT data were not corrected for inertia of theflywheel'8. However, power measurements were notinitiated until swimmers had attained unresistedacceleration of the ergometer flywheel in accordancewith the methodology of a previous studyl'.The MPO consisted of arm cranking at 80 r.p.m.

against a progressively increasing workload untilvolitional fatigue. The initial work rate was24Wmin- for males and 16Wmin-' for females.The power output was increased every 2 min by 16Wuntil subjects could no longer maintain a cadence of70 r.p.m. For each test WLpeak was defined as thehighest workload the subject completed. If a work-load was not completed, WLpeak was determinedfrom the following formula:

WLpeak (W) = WLcom + (t/120 x AWL) (1)where WLcom was the last workload which the subjectcompleted for 120 s, t was the time(s) the finaluncompleted workload was sustained and AWL wasthe final workload increment.

Subjects rested for 24 h before testing. During boththe upper body tasks, subjects were instructed toremain seated, and during all laboratory tests theywere given strong verbal encouragement.

Anthropometric dataSkinfold measurements were taken at the biceps,triceps, suprailiac, subscapular, mid-axilla, pectoral,abdominal, thigh and calf folds'9. Lean body mass(LBM) and percentage body fat (% fat) wereestimated from skinfold measurements20. Arm length(AL) and leg length (LL) were also measured. AL wastaken as the distance from acromion to stylion and LLwas taken as the distance from trochanterion tosphyrion'9.

Swimming performanceTimed swims were performed within 72 h of labora-tory testing in a 25-m (short-course) pool. Subjectsarrived at the pool and undertook a warm-upsupervised by their coach. The 50-m time-trial wasconducted first with a recovery period of 60 minbefore the 400-m swim. Subjects began the swim inthe water with timing being started manually whentheir feet left the wall of the pool. Subjects wereinstructed to produce maximal effort. Three indepen-dent assessors recorded the swim times with theaverage of these being taken as representative of each

subject's performance. Times were subsequentlyconverted to speeds (S) for the two swim distances.The number of strokes taken per length was alsorecorded in order to calculate the distance coveredwith each stroke (DS, m stroke-'). Although thismethod overestimates DS by 4-5% due to the pushoff from the side of the pool2l, this is a systematicoverestimation which does not greatly influencesubsequent comparisons between swimmers'2.Therefore, in accordance with previous studies2223no attempt was made to derive a correction factor forDS. A stroke index (SI) was determined as previouslydescribed by Costill et al.24.

Statistical analysisPearson product moment correlations and multiplelinear regression analyses were performed using thecomputer software package SYSTAT (Systat, Evans-town, Illinois). Results were considered significantwhere P < 0.05.

ResultsThe physical characteristics of the subjects aredisplayed in Table 1. With the exception of LBM therewere no significant differences between male andfemale swimmers for the characteristics measured.

Table 2 shows the performance data for the 50-mand 400-m timed swims. Sprint-swim performancesfor 50m ranged from 1.39ms-1 to 1.85ms-1 formales and from 1.42ms-1 to 1.79ms-1 for females,indicating a wide variation in sprint-swim ability.Both S50 and DS50 were significantly greater (P <0.05) for males than females. There were, however,no significant differences with respect to S400 andDS400.

Table 3 displays the power output values for theupper and lower body WAT and MPO. Significant

Table 1. Descriptive characteristics of swimmers

Subjects Age Body mass LBM Body fat(years) (kg) (kg) (%)

Males (n = 12) 13.6(1.2) 54.4(7.6) 44.3(8.2) 18.6(4.9)Females (n = 10) 13.2(1.9) 56.2(10.1) 41.9(6.6) 25.4*(4.1)

Values are mean(s.d.); LBM, lean body mass*Significantly greater than for males, P < 0.05

Table 2. Performance characteristics of the sprint and middle-distance swims

Subjects S50 DS50 S400 DS400(m s-1) (m stroke-1) (ms-1) (mstroke-1)

Males 1.69*(0.15) 1.26*(0.13) 1.34(0.12) 1.12(0.23)Females 1.55(0.12) 1.11(0.13) 1.27(0.09) 1.08(0.07)

Values are mean (s.d.); S50, swim speed over 50 m; DS50,distance covered with each stroke during the 50-m swim; S400,swim speed over 400 m; DS400, distance covered with each strokeduring the 400-m swim.*Significantly greater than for females, P < 0.05

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Table 3. Power outputs for the Wingate Anaerobic Test and the maximum sustained power output test

Upper body Lower body

PP MP WLpeak PP MP

Males 4.89*(0.59) 3.74*(0.36) 1.75(0.46) 10.75t(O.94) 8.26(0.97)Females 3.65 (0.47) 2.82(0.29) 1.39(0.39) 9.51(0.%) 6.58(0.78)

All values, expressed inW kg-', are mean(s.d.) PP, peak power; MP, mean power; WLpeak, peak sustained workload*Significantly greater than for females, P < 0.001tSignificantly greater than for females, P < 0.01

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Mean arm power (W kg 1)Figure 1. Relationship between sprint-swim speed (S50)and mean power of the arms (MP5rnz5) for male (M) andfemale (F) swimmers. r = 0.63; y = 0.163x + 1.087; s.e.e. =0.121; n = 22

differences in power output were found betweenmale and female swimmers for peak power of thearms (PPr; P < 0.001), mean power of the arms(MPa,, P < 0.001), peak power of the legs (PPIegs; P< 0.01) and mean power of the legs (MPlegs; P <0.001). There were no significant differences betweenmale and female subjects with respect to WLpeak.

Figure 1 shows the relationship for S50 and MPary,along with the associated regression equation, whileFigure 2 displays the relationship betwen S50 andMP, s. Multiple regression analysis revealed thatWA? indices for the arms or the legs did notsignificantly increase the explained variance in S50above that of each separately. Further, gender did notadd significantly above WAT power indices in theprediction of sprint-swim speed and therefore singleregression lines combining both males and femalesare displayed.

Step-wise multiple regression analysis revealed thebest predictors of S50 were MPiew DS50 and AL(r =0.956, P < 0.001; s.e.e. = 0.48).

Figure 3 displays the relationship between S400 andWLpjeak for male and female subjects, along with theassociated regression equation.

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Figure 2. Relationship between sprint-swim speed (S50)and mean power of the legs (MPiegj) for male (M) andfemale (F) swimmers. r = 0.76; y = 0.93x + 0.928; s.e.e. =

0.100; n = 22

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Peak sustained workload (W kg 1)Figure 3. Relationship between middle-distance swimspeed (S400) and maximal sustained workload (WLpeak) formale (M) and female (F) swimmers. r= 0.70; y = 0.167x +1.051; s.e.e. = 0.086; n = 22

Br J Sp Med 1992; 26(3) 153

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DiscussionThis study shows that strong relationships existbetween upper and lower body power output andboth sprint (50 m) and middle-distance (400 m)freestyle-swim performance.

In the absence of longitudinal stature data,ancillary evidence of secondary sex characteristicsand age of menarche, we, cannot explain any variancein physiological and performance parameters whichmay be due to differences in the level of maturation ofour swimmers'9. Therefore, we have considered thedata from the standpoint of the chronological age ofour subjects only.Our correlation of 0.63 between MParms and S50 is

somewhat lower than previously reported',7,1.Further, Inbar and Bar-Orl2 found that for untrainedchildren, anaerobic performance with the arms was60-70% of that achieved by the legs; in the currentstudy the corresponding figure was only 45%. Thus,there appears to have been a reduction in the ratio ofarm to leg power in our subjects. This may, in part,explain why the relationships between the WATpower indices for the lower body and S50 werehigher than those found for the upper body. Thepossibility also exists that the 'normal' arm:leg powerratio in untrained children'2 is different in swimmers.

Alternatively, the different ratio of arm:leg powerfound in the present study may be related to thelong-distance swim-training our subjects were under-taking, which has a primary reliance on the arms'srather than the legs. As noted by Costill et al.26, it isnot uncommon for swimmers to experience a markedreduction in muscle power during periods of intensetraining, which can subsequently be reversed by areduction in training volume.Our correlation of 0.76 between MPIegs and S50 is

also lower than the figure of 0.90 reported by Inbarand Bar-Or7. The discrepancy between the twocorrelations can probably be attributed to thedifferent criterion swim distances to which poweroutput was related. The study of Inbar and Bar-Or7employed a 25-mi sprint-swim, whereas a distance of50m was chosen for the current investigation.However, as noted previously', large subject num-bers would be required to provide the statisticalpower necessary to detect small differences betweencorrelation coefficients.The highly significant relationship (r = 0.70, P <

0.001) found between WL eak and S400 in the presentstudy is notable. It has been suggested2-5 that thevariable that best predicts endurance performance isthe highest workload an athlete attains during amaximal test. Noakes et al.4 and Scrimgeour et al.5found that for running, the peak treadmill speedachieved in a maximal test was a better predictor ofperformance than Vo2ma,,. Recently, Hawley andNoakes2 reported a highly significant relationship(r = 0.91, P < 0.001) between the peak power a cyclistattained during an exhaustive laboratory cycling testand a 20-km cycle time-trial. Further, Costill et al.24report only a moderate relationship (r = 0.43)between a swimmer's time in an all-out 400 yard(365.8 m) swim, and VO2max. We have previouslyobserved that the correlation between Vo2max deter-

mined during the MPO laboratory test and S400 is inthe order r = 0.42-0.48 (Hawley et al., unpublishedobservations), which is almost identical to therelationship found by Costill et al.24 for VO2maxmeasured after a 400 yard maximal swim.

In our own preliminary studies we have noted thatthe fastest swimmers not only display high anaerobicpower outputs but also high peak sustained poweroutputs, as determined by the WLpeak they achieveduring a progressive, incremental maximal armpower test (Hawley and Williams, unpublishedobservations). In the present investigation the rela-tionship between .MParms and WLpeak was 0.55 (P <0.01). Jones and McCartney27 have previously re-ported a high relationship between VO2max and totalwork output during 30 s of maximal isokineticexercise. These workers suggested that 'changes inmuscle function' could contribute to increases inmaximal short-term work capacity evidenced after aperiod of training.With respect to sprint-swimming speed and stroke

mechanics, males were faster (P < 0.05) and covereda greater distance (P < 0.05) with each stroke thanfemales. Correlations between DS50 and S50 were0.93 for males and 0.82 for females. Other studies-24have indicated the importance of DS in determining aswimmer's speed.The single best predictor of sprint-swim perform-

ance in the present study was the swimmer's strokeindex (SI50; r = 0.97 for males, r = 0.94 for females).The SI (S x DS) assumes that for a given speed theswimmer who has the greatest DS has the mostefficient swimming technique24. The SI is obviouslysensitive to a swimmer's biomechanical and technicalcompetence. Unfortunately, however, the SI cannotbe considered an independent predictor of S50 sincethe derivation of this parameter incorporates S50.With regard to middle-distance performance, there

were no significant differences between males andfemales for S400 and DS400. Correlations betweenDS400 and S400 in the present study (r = 0.42 formales, r = 0.43 for females) are lower than thosereported by Costill et al.24. These workers found thesingle best predictor of swim performance over 400yards (365.8 m) in male and female competitiveswimmers was DS400 (r = 0.88). The best predictor ofmiddle-distance swim performance in the presentinvestigation was the peak workload the subjectattained during the MPO test (r = 0.70, P < 0.001).The relationship between S50 and S400 in the

current study was strong (r = 0.80 for males, r = 0.38for females), and illustrates that speed is still a largecomponent of the 400-m event. Sharp et al.9 found analmost identical correlation (r = 0.82) between 25yard (22.86 m) sprint velocity and 500 yards (457.2 m)time and suggested that 'arm power' was a necessarycomponent for success in the longer distance event.In summary, this study has demonstrated that

significant relationships exist between laboratorymeasures of power and swim performance over bothsprint and middle-distance events. Although ourstudy cannot determine whether the relationshipbetween our laboratory measures of power and swimperformance are causal or merely coincidental,previous studies9'29 reveal that for the upper body

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the relationship is likely to be causal2. - Further,previous investigations with swim-power tests haveshown that small differences in musde power areassociated with measurable performance improve-ments in freestyle sprint-swimming29-31. Therefore,swimmers in events up to 400m may benefit fromtraining which aims to improve arm and leg power. Inthose swimmers who possess a high level of arm andleg power, factors such as stroke mechanics maycontribute more to the differences in performanceseen between these individuals.As the majority of individual swim events have a

major reliance on anaerobic metabolism32, the neces-sity for large volumes (>10 000m day-') of moderateintensity 'aerobic overload training' for these athletesmust be seriously questioned. As recently noted byCostill et al. 3 'it is difficult to understand howtraining at speeds that are markedly slower thancompetitive (race) pace for 3-4h day-1 will preparethe swimmer for the supramaximal efforts of com-petition'.Taken collectivel , the results of the current and

other studies', 726 31 suggest that 'muscle power' isan important determinant of both sprint and middle-distance swimming performance. Although themechanisms underlying the relationship between'muscle power' and swimming performance cannotbe explained by the current study, future investiga-tions should focus on the examination of differenttraining regimens and their influence on musdecontractility3. Such training studies will help eluci-date those factors responsible for performancedifference between individuals.

AcknowledgementsThis study was supported by a grant from Fitness Concepts(NZ) Limited.

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