cronin & sleivert (2005)

Sports Med 2005; 35 (3): 213-234REVIEW ARTICLE 0112-1642/05/0003-0213/$34.95/0

2005 Adis Data Information BV. All rights reserved.

Challenges in Understanding theInfluence of Maximal Power Trainingon Improving Athletic PerformanceJohn Cronin1 and Gord Sleivert2

1 New Zealand Institute of Sport and Recreation Research, Auckland University of Technology,Auckland, New Zealand

2 Human Performance Laboratory, Faculty of Kinesiology, University of New Brunswick,Fredericton, New Brunswick, Canada

ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2131. Seminal Training Practice and Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2142. Power-Load Spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215

2.1 Upper Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2162.2 Lower Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219

3. Power and Performance: Cross-Sectional Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2203.1 Upper Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2223.2 Lower Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

3.2.1 Cyclic versus Acyclic Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2223.2.2 Absolute versus Relative Power Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2243.2.3 Maximum Power versus Power Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2243.2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

4. Power and Performance: Training Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2265. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232

The ability to optimise muscular power output is considered fundamental toAbstractsuccessful performance of many athletic and sporting activities. Consequently, agreat deal of research has investigated methods to improve power output and itstransference to athletic performance. One issue that makes comparisons betweenstudies difficult is the different modes of dynamometry (isometric, isokinetic andisoinertial) used to measure strength and power. However, it is recognised thatisokinetic and isometric assessment bear little resemblance to the accelerative/decelerative motion implicit in limb movement during resistance training andsporting performance. Furthermore, most people who train to increase powerwould have limited or no access to isometric and/or isokinetic dynamometry. It isfor these reasons and for the sake of brevity that the findings of isoinertial(constant gravitational load) research will provide the focus of much of thediscussion in this review.

One variable that is considered important in increasing power and performancein explosive tasks such as running and jumping is the training load that maximises

214 Cronin & Sleivert

the mechanical power output (Pmax) of muscle. However, there are discrepanciesin the research as to which load maximises power output during various resistanceexercises and whether training at Pmax improves functional performance isdebatable. There is also some evidence suggesting that Pmax is affected by thetraining status of the individuals; however, other strength variables could quitepossibly be of greater importance for improving functional performance. If Pmaxis found to be important in improving athletic performance, then each individual’sPmax needs to be determined and they then train at this load. The predilection ofresearch to train all subjects at one load (e.g. 30% one repetition maximum[1RM]) is fundamentally flawed due to inter-individual Pmax differences, whichmay be ascribed to factors such as training status (strength level) and the exercise(muscle groups) used. Pmax needs to be constantly monitored and adjusted asresearch suggests that it is transient. In terms of training studies, experiencedsubjects should be used, volume equated and the outcome measures clearlydefined and measured (i.e. mean power and/or peak power). Sport scientists areurged to formulate research designs that result in meaningful and practicalinformation that assists coaches and strength and conditioning practitioners in thedevelopment of their athletes.

1. Seminal Training Practice 1RM. Higher tensions would inhibit the ability ofand Research muscles to move quickly, which was thought a

fundamental prerequisite of power training.Power can be defined as the amount of work

In contrast, some coaches have thought heavierproduced per unit time or the product of force andloads are necessary for improved power production.velocity. The development of power and its transfer-Poprawski[3] compared the strength power results ofence to performance has been the source of interestEdward Sarul, 1983 World Champion in the shot-and discussion for years. Initially, coaches andput, to nine well trained shot-putters, which includedstrength and conditioning practitioners debated the>21m throwers. While Sarul was slightly strongermerits of using various loads for the development ofthan the group average in the bench press (1.4%),power. From the literature there appeared twosnatch (7.9%), power clean (5.3%) and squatschools of thought, one that was Western in origin(7.8%), the major differences occurred in tests ofand espoused the use of lighter loads (<50% onespeed and power at heavy loads in those respectiverepetition maximum [1RM]) for improving powerexercises. For example, Sarul’s snatch velocityoutput and athletic performance, whereas Easternranged from 4.13% faster at 20kg than the averagebloc coaches and trainers proposed that heavierto 22.13% faster at 80kg. Similarly, his squat veloc-loads (50–70% 1RM) were superior. For example,ity was 2.74% greater at 40kg but 25.71% greater atCounsilman[1] a sport scientist and swimming coach,140kg. These findings led Poprawski[3] to concludeargued that athletes needed to move light loads atthat movement velocities at higher loads (50–70%high speed, as fast movements activated the fast1RM) were critical determinants of athletic successfibres. Conversely, slow training recruited fibresin athletes and training emphasis should be placedwith slow contraction characteristics, which wason moving lighter loads (50% 1RM) quickly, ratherthought counter-productive to power training. Simi-than just striving to lift more weight. Spassov[4] in alarly, Behm,[2] in discussing the use of surgicaldiscussion of programme design for athletes, statedtubing for a tennis power programme, suggested thatthat experts believe loads of 50–70% 1RM per-this should be combined with traditional weightformed at a maximal rate, develop explosive power.training incorporating loads of not more than 50%

2005 Adis Data Information BV. All rights reserved. Sports Med 2005; 35 (3)

Maximal Power Training and Improving Athletic Performance 215

Verkhoshansky and Lazarev[5] in a discussion of example, Edgerton et al.,[11] discussing the effects ofmuscle architecture, depicted maximum power out-Eastern bloc principles for the training of speed andput (Pmax) occurring at a range of isometric forcesstrength believed also that loads of 50–70% 1RMdepending whether the knee extensors (45%), kneewere necessary for the development of ‘explosiveflexors (59%), plantar flexors (35%) and dorsiflex-strength’. Tidow[6] suggested that heavy loads mightors (53%) were studied. These differences werebe equally as effective as light loads for stimulatingattributed to different fibre lengths that make deter-fast motor unit activity, as the fastest high thresholdmination of Pmax difficult, as Pmax is related to fibreunits need to be recruited to lift heavy loads. Thisshortening velocity, which in turn is related to thedichotomy as to which loads (light vs heavy) bestnumber of sarcomeres arranged in series (fibremaximise power development remains topical and islength). In fact, Edgerton et al.[11] concluded that thestill the source of much research, but clearly therecomplication of variable fibre lengths makes anywas a dichotomy of opinion between Eastern andconclusion regarding power per unit of muscleWestern bloc power training philosophies.weight per muscle group of limited value. It wouldOne approach to solving this dichotomy is toseem some of the previous assumptions made bystudy the relationship between force and velocity,other authors, based on these research findings, are

since power is the product of both these variables. Itmisplaced. Additionally, it would seem that study-

is well known that as load increases, the force outputing the power output of whole muscle in vivo would

of muscle in concentric contractions increases with ahave greater practical significance to athletes,

concomitant decrease in the velocity of shortening.coaches and trainers. The power outputs across a

This phenomenon is known as the force-velocityspectrum of loads (power-load spectrum) using dy-

relationship of muscle.[7] It is thought that maximumnamic multiarticular exercises similar to those used

power output is the product of optimum force andduring weight training need to be examined, the

optimum shortening velocity. For isoinertial con-results of which should give a greater appreciation

tractions, it has been suggested that maximum pow-of the load that maximises mechanical power output

er output occurs at approximately 30% of maximum in a functional context.shortening velocity or at approximately 30% ofmaximum isometric force.[7,8]

2. Power-Load SpectrumMany researchers have endorsed such loading for

maximising power output[9,10] citing the research of When studying the power-load relationship, oneEdgerton et al.,[11] Faulkner et al.[12] and Kaneko et must be cautious of extrapolating findings from theal.[13] as support for the utilisation of such loads. literature since some research has investigated theHowever, closer scrutiny of this research leaves one power-load relationship indirectly. That is, the rela-thinking that such conclusions are somewhat mis- tionship between load and power has been investi-leading. For example, Faulkner et al.[12] certainly gated, but the load that maximised power output wasreported peak powers at approximately one-third of not reported. For example, using subjects from amaximal shortening velocity; however, they do not weight-training class, Mastropaolo[14] measuredstate at what relative force peak power output occurs power output across loads of 20–100% 1RM. It was(the reader having to extrapolate this information reported that subjects were tested using a bench-from the graphs provided). Whether power differs press motion, although the figure depicting the exer-significantly across the power-force spectrum is, cise appears to be a shoulder-press machine. None-therefore, unclear. In fact, the power profile of slow theless, power profiles based on this movement areand mixed muscles appears similar across loads of detailed in graphical form and the authors concluded15–50% maximum isometric force.[12] Furthermore, (without any apparent statistical support) that thewhether such findings are applicable to whole mus- load maximising power output occurred at 40%cle or biarticular movement is questionable. For 1RM. However, loads from 40% to 60% 1RM ap-



pear very similar in power output. Making such in table I. In all cases, derivatives of the bench pressinterpretations without statistical analysis is prob- have been used to study the power-load relationship.lematic. As can be observed from table I, the loads reported

The findings of another often-cited paper that to optimise Pmax are similar irrespective of subjectinvestigated the power-load relationship[13] also training status, age and the type of bench-pressneed to be interpreted with caution. In this study, 20 motion used. Most studies report a band in whichmale subjects were allotted to four training groups Pmax occurs, some research also indicating thatbased on their maximum isometric strength. They loads either side of this band are not significantlytrained their elbow flexors using either isotonic (0%, different.[15,16] It would seem then that the majority30% or 60%) or isometric (100%) contractions. of research reports loads of 30–70% 1RM as thePeak power of the elbow flexors during concentric intensities that maximise mean and peak power out-muscle actions was observed at intermediate move- put.ment velocities of approximately 30% of maximum Three observations from table I appear notewor-shortening velocity and 30% of maximum isometric thy. First, greater power outputs are associated withstrength.[13] These authors justifiably chose to ex- the professional and semi-professional rugby leagueamine the effects of three loads on Pmax. However, players, which is no doubt a function of their greatersuch a design does not mean that 30% 1RM is the body mass, training status (maximal strength) and,load that maximises power output. The load that therefore, greater relative loads used for the calcula-maximised power output could be anywhere be- tion of Pmax. For example, Baker et al.[15] reportedtween 30–60% of maximum isometric force, yet mean body mass and 1RM of 92.0 ± 11.1kg andmany authors[9,10] continue to cite this study as sup-

129.7 ± 14.3kg, respectively, whereas Cronin etport for light loads (30%) producing maximal

al.[16] reported 89 ± 2.5kg and 86.3 ± 13.7kg, respec-mechanical power output. Furthermore, uniarticular

tively, for club rugby players. Nonetheless the bandmotion was examined in this study and untrained

of loads that maximised mean power output wassubjects were used, which limits generalisability to

very similar, although ironically it appears that theathletic populations. Also, maximal mechanical dy-

Pmax of the better trained (greater maximal strength)namic power output was reported based on a per-

rugby league players occurred at a lower percentagecentage of maximal isometric force with no esti-

of their 1RM. Secondly, it may be that the load thatmates of power in relation to the actual dynamic

maximises peak power is slightly greater than theexercises used in strength training (e.g. squat and

load that maximises mean power output. The find-bench press) or the athletic performance itself. It isings for the lower body (see table II) would certainlyquite likely that the force at which Pmax occurssupport this contention. Thirdly, and related to thediffers, if expressed relative to a dynamic strengthfirst point, it would appear that Pmax may be tran-measure (% 1RM). Based on these observations, itsient and is affected by the strength status of theseems that the assumption of many authors that apopulation being studied. Mayhew et al.[17] reported30% 1RM load maximises power output remainsthat 12 weeks of weight training increased power atproblematic. Investigating the power-load spectruma fixed absolute load (Pmax increased). Presumably,using dynamic (isoinertial) multiarticular motionas the athletes became stronger, the absolute loadwould appear to have greater practical significancebecame lighter and consequently could be liftedto strength and conditioning practitioners and sportwith greater speed. Thus, the increase in Pmax fromscientists alike.40% to 50% 1RM was due to a 10% increase inmaximal strength. However, this does not seem the

2.1 Upper Bodycase when relative loads are used.

Baker et al.[15] found that the percentage 1RMThe upper-body mean and peak power outputsassociated with a spectrum of loads can be observed that maximised power output was significantly low-


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Table I. Loads that maximised mean and peak power output for the upper body

Study Subjects Power measure Maximum power output Maximum power output(% 1RM or load) (W) [mean ± SD]

Mean power output

Baker[18] 22 M professional rugby league players Concentric-only BP throw across loads 40, 50, NRL: 70kg (51% 1RM) NRL: 600 ± 83(NRL) 60, 70 and 80kg SRL: 60kg (55% 1RM) SRL: 502 ± 7827 M college-aged players (SRL)

Baker et al.[15] 31 professional and semi-professional Concentric-only BP throw across loads 40, 50, 55% 1RM 598 ± 99rugby league players 60, 70 and 80kg 46–62% 1RMa

Cronin et al.[16] 27 M club rugby players Concentric and rebound BP and concentric and 50–70% 1RM 211–356rebound BP throws across loads of 30, 40, 50,60, 70 and 80% 1RM

Izquierdo et al.[19] 26 middle-aged (mean age 42y) and 21 Concentric only and stretch-shorten cycle BP 30–45% 1RM for both 237–293elderly M (mean age 65y) across loads of 0, 30, 45, 60 and 70% 1RM age groups

Izquierdo et al.[20] 70 M weightlifters, middle-distance Concentric only BP across loads of 30, 40, 50, 30–45% 1RM 200–391runners, handball players, cyclists and 60, 70, 80, 90 and 100% 1RM 2.82–4.86 W/kgcontrols

Newton and Wilson[21] 45 M with at least 6mo bench-press Rebound BP throws across loads of 10, 20, 30, 30–40% 1RMtraining experience 40, 50, 60, 70, 80, 90 and 100% 1RM

Newton et al.[9] 17 M exercise science students with Concentric only and rebound BP throws across 30–45% 1RM 560–5636mo weight training experience loads of 15, 30, 45, 60, 75 and 90% 1RM

Peak Power Output

Bemben et al.[22] 31 M college students Rebound BP across loads of 30, 40, 50, 60, 70 50% 1RMand 80% 1RM

Cronin et al.[16] 27 M club rugby players Concentric and rebound BP and concentric and 50–60% 1RM 463–626rebound BP throws across loads of 30, 40, 50, 40–70% 1RMa

60, 70 and 80% 1RM

Mayhew et al.[17] 21 M college students Rebound BP across loads of 30–80% 1RM 40% 1RM pre-intervention50% 1RM after subjectsincreased strength

Siegel et al.[23] 25 M college students BP across loads of 30, 40, 50, 60, 70, 80 and 40–60% 1RM ~500b

90% 1RM

a Similarly effective to loads that maximised power output.

b Extrapolated from graph.

1RM = one repetition maximum; BP = bench press; M = male; NRL = national rugby league; SRL = student rugby league.

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Table II. Loads that maximised mean and peak power output for the lower body

Study Subjects Power measure Maximum power output Maximum power output(% 1RM) (W) [mean ± SD]

Mean power output

Baker et al.[24] 32 professional and semi-professional JS across loads of 40, 60, 80 and 100kg – 55–59% 1RM 1851 ± 210rugby league players system mass 47–63% 1RMa

Izquierdo et al.[19] 26 middle-aged M (mean age 42y) and Concentric only and stretch-shorten cycle half- 60–70% 1RM for both 391–48621 elderly M (mean age 65y) squats across loads of 0, 30, 45, 60 and 70% age groups

1RM

Izquierdo et al.[20] 70 M subjects – weightlifters, middle- Concentric only half-squats across loads of 30, 45–60% 1RM 385–755distance runners, handball players, 40, 50, 60, 70, 80, 90 and 100% 1RM 5.5–9.43 W/kgcyclists and controls

Sleivert and 30 M rugby, rugby league and SS and TS across loads of 30, 40, 50, 60 and SS: 30–60% 1RM 7.32 ± 1.34 W/kgTaingahue[25] basketball players 70% 1RM TS: 30–60% 1RM 7.07 ± 1.25 W/kg

Weiss et al.[26] 31 M fitness-trained lifters Concentric-only parallel squats across loads of 30% 1RM 1011 ± 10030, 60 and 90% 1RM

Peak power output

Bourque and Sleivert[27] 16 males (eight power [six volleyball, Parallel concentric JS across loads of 0, 30, 40, Mean: 14% 1RM Mean: 5216 ± 1234two badminton], eight endurance 50, 60, 70% 1RM Mode for power Power: 6117 ± 867athletes) Body mass included athletes 0% 1RM; Endurance: 4315 ± 808

mode for enduranceathletes 30% 1RM

Esliger and Sleivert[28] 21 (11 M and 10 F) volleyball and Parallel concentric JS across loads of 30, 40, 63% 1RM 1766 ± 479basketball players 50, 60, 70 and 80% 1RM

Siegel et al.[23] 25 M college-aged students Squats across loads of 30, 40, 50, 60, 70, 80 50–70% 1RM ~950b

and 90% 1RM

Sleivert and 30 M rugby, rugby league and SS and TS across loads of 30, 40, 50, 60 and SS: 30–60% 1RM 17.10 ± 3.15 W/kgTaingahue[25] basketball players 70% 1RM TS: 50–70% 1RM 17.58 ± 2.85 W/kg

Stone et al.[29] 10 subjects with a range of training JS and CJ across loads of 10, 20, 30, 40, 50, Weakest subjects: 10% JS: 3482 ± 443experience (7wk to >15y) 60, 70, 80, 90 and 100% 1RM 1RM CJ: 3785 ± 376

Strongest subjects: JS: 5635 ± 257740% 1RM CJ: 5391 ± 2566

Thomas et al.[30] 19 untrained F Double leg-press 56–78% 1RM 404 ± 22

Weiss et al.[26] 31 M fitness-trained lifters Concentric only squats (parallel) 60% 1RM 1711 ± 188

a Similarly effective to loads that maximised power output.

b Extrapolated from graph.

1RM = one repetition maximum; CJ = countermovement jump; F = females; JS = jump-squats; M = males; SS = split jump-squats; TS = traditional jump-squats.


er in professional compared with state and city- calculation and, consistent with the results of Bour-league college-aged rugby league players (see table que and Sleivert,[27] their calculated mean powerI). Reanalysed data from Baker’s previous research values are much higher than other mean powerconfirmed this finding, the strongest national league values reported in the literature. The relative load atplayers used significantly lower resistances of 47% which they reported mean power to be maximal was,1RM compared with the 54% 1RM of less strong however, much higher than that reported in Bourquenational league players.[31] It would seem as athletes and Sleivert’s study and consistent with the otherbecome stronger they can produce greater power literature. Nevertheless, it should be noted that Bak-outputs with any absolute load, but the ability to er et al.[24] did not measure power output at loadsproduce power at a given percentage of their 1RM lighter than 40kg on the bar, so it seems likely thatremains similar as relative resistances increase pro- mean power could have been higher at lighter loadsportionally to maximum strength levels. using this method of calculation.

Other studies have used different calculations to2.2 Lower Body study the load-power relationship. Sleivert and Ta-

ingahue[25] calculated net power as force exertedIn terms of the lower body, the mean and peak

into the bar by the subject: (bar weight + [bar mass ×power outputs associated with a range of loads can

acceleration by subject]) × velocity of bar. It appearsbe observed in table II. The power outputs are

that Izquierdo et al.[20] and Weiss et al.[26] calculatedreported for a greater variety of movements com-

power output by simply using bar mass relative topared with the upper body, and female power out-

1RM. The variety of methods used to calculate theputs are also represented. The research of Thomas et

power output makes inter-individual comparisonsal.[30] reported a higher Pmax (56–78% 1RM) than

between studies difficult. Clearly a standard methodmost other research, which could be attributed to the

for calculating power in resistance training move-subject’s untrained status, female sex or the differ-

ments needs to be agreed upon. In the meantime,ent movement used (double leg press). However, in

researchers and practitioners should be aware of theterms of the squat and its derivatives, no clear trendsimplications resulting from including or excludingare observable between training status, sex, age orbody mass in power calculations for exercises oc-type of exercise used. Most studies report acurring in the vertical plane. It seems reasonable to‘bandwidth’ of loads that maximise power output.include body mass as part of the resistance athletesAlso, unlike in upper-body exercises, peak powerare working against for exercises occurring in thehas been reported in some instances to occur with novertical plane. If body mass is not taken into accountextra load on the bar (unweighted) or only a lightwhen calculating the load for subjects/athletes, inap-load (10–20% 1RM).[27] Bourque and Sleivert[27]

propriately heavy loads may be selected for jump-recently reported power results much higher and atsquats. For upper-body exercises, only a fraction oflighter relative loads than other studies in the litera-body mass is propelled, therefore, the load-powerture that have reported lower peak power to occur atrelation is potentially different and mean and peakheavier relative loads. This is because body masspower are likely to occur at higher relative loads.has been included as part of the resistance the ath-

Besides incorporating body mass into the powerletes are propelling in the jump-squat. When usingcalculations, there are two other reasons why bothballistic motion such as jump-squats, it is thoughtBaker et al.[24] and Bourque and Sleivert[27] reportedappropriate to use system mass to calculate loadinghigh power outputs in trained power type athletes.intensity, as the subject must propel themselves asFirst, jump-squats were used in both these studies,well as the bar. Excluding body mass from theand ballistic motion of this type has been shown toequation decreases the total mass component ofincrease power output compared with traditionalforce, therefore, decreasing total power output. Bak-

er et al.[24] also included body mass in their power weight-training movements as used by Izquierdo et



al.[20] and Weiss et al.[26] where there is no projection detail the loading parameters specific to each indi-vidual exercise and that this be based on 1RMof oneself or the bar.[16,32] Secondly, specific neuro-assessment similar to the range of motion beingmuscular adaptations (higher maximal strength orprescribed for power training. Qualifying this state-maximum velocity of contraction) may have influ-ment, prescription of the load that optimises Pmaxenced Pmax. In the recent dissertation of Bourqueneeds to be determined for each individual per exer-and Sleivert,[27] the major difference in jump-squatcise. Research reports the mean response (% 1RM =power between power and endurance athletes wasPmax) for the population being studied, but thethe ability of the power athletes to increase the‘bandwidth’ approach to reporting Pmax adopted byvelocity of movement at light loads. Endurance ath-most research suggests that there is a range of loadsletes could not increase the velocity of movementthat maximise power output or more likely that thereand, therefore, power decreased markedly as loadare large inter-individual differences in Pmax.decreased.

As stated earlier in this section, the method of3. Power and Performance:calculating Pmax has a large influence on both abso-Cross-Sectional Researchlute power values and the power-load relationship.

Additionally, the relative load that maximises peakTheoretically, the best improvements in athletic

power appears higher than the load that maximises tasks that involve significant power output (jump-mean power. Furthermore, it seems that these fac- ing, sprint, agility and lunge performance) would betors may be influenced by the type of exercise gained by training at the load that maximised anperformed.[25,30] The previously discussed results of individual’s power output using an exercise similarEdgerton et al.[11] (see section 1) would support such to their athletic activity. However, this presumesa contention given that Pmax occurred at different that power is the best predictor of athletic perform-isometric forces depending whether the knee exten- ance and, therefore, it is training to improve powersors (45%), knee flexors (59%), plantar flexors output that will best facilitate improved perform-(35%) or dorsiflexors (53%) were used. Therefore, ance. Such an assumption may be misplaced princi-different exercises (muscle groups) may conceiva- pally because of the diversity of strength/powerbly have differential power outputs. However, measures, flawed methodologies and misrepresent-Sleivert and Taingahue[25] explain the differences in ed research findings. For example, literature dealingmaximal peak power between the split and tradition- with the development of power tends to mix termi-al jump-squats reported in their study as being a nology using such terms as power, rate of forceresult of the different starting position of both exer- development (RFD), explosive strength (maximumcises. That is, the 1RM for the low start position of force/time to achieve maximum force) and/or im-the traditional squat (149.5 ± 22.6kg) was signifi- pulse interchangeably. One needs only to read somecantly less than for the split squat (206.6 ± 34.4kg). reviews in this area to observe the confusion, powerAs a result of the low start position of the traditional has been associated with the ability to exert greatsquat, the load was difficult to move initially, but force in a short amount of time (impulse)[33] andcomparable velocities to the split squat were confused with explosive strength or rate of forceachieved later in the lift. Through the range of development.[34] Newton and Kraemer,[35] in consid-movement in which peak power occurred, both ering methods to increase muscular power, devotesquats had similar bar velocities and absolute loads, much of their discussion to the importance andalthough relative loads were very different. There- development of RFD. Sapega and Drillings,[36] in afore, traditional squat peak power was maximal at a discussion of the confusion that abounds concerninghigher relative load to that of the split squat. It was the measurement of power, detail how one group ofconcluded that the prescription of maximal power authors have calculated peak power by dividingtraining using different exercises and ranges should peak torque by the duration of the contraction and



Table III. Intercorrelation matrix between traditional strength and power measures and Zatsiorsky’s measures of explosive strength[40]a

IES RC SG AG MP PP MF PF I100 MS

IES *

RC 0.84 *

SG 0.85 0.68 *

AG 0.80 0.76 0.55 *

MP 0.75 0.43 0.76 0.54 *

PP 0.74 0.45 0.73 0.60 0.99 *

MF 0.80 0.55 0.62 0.52 0.88 0.85 *

PF 0.86 0.61 0.69 0.63 0.92 0.90 0.99 *

I100 0.80 0.54 0.53 0.51 0.89 0.86 0.99 0.99 *

MS 0.81 0.56 0.69 0.57 0.85 0.83 0.94 0.94 0.94 *

a All correlations are statistically significant at p ≤ 0.05.

AG = acceleration gradient; I100 = impulse at 100ms; IES = index of explosive strength; MF = mean force; MP = mean power; MS =maximal strength; PF = peak force; PP = peak power; RC = reactivity coefficient; SG = starting gradient; * indicates 100% perfectcorrelation.

two other studies have used initial RFD as measures activity coefficient, start-gradient and acceleration-of power.[36] gradient)[39] can be observed from table III. The

relationship of these measures of explosive strengthMisused terminology and misrepresented re-to more traditional measures of force and powersearch findings are also prevalent in the literature. Insuggest that the measures of explosive strength fora study of 8–12RM weight training performed atthe most part measure different strength qualitiesdifferent execution speeds, Young and Bilby[37] de-than more traditional measures. In particular, thescribed their two power measures as maximum RFDreactivity coefficient (r = 0.43–0.61) and A-gradientand jump height. Neither measure is representative(r = 0.52–0.63) have less of their variance explainedof power output. Indeed, leg power is generally notby force and power.strongly correlated to jump height and there are

limitations in extrapolating results from functional Progressing this contention, it may be that thetests such as vertical jump to reflect power. Addi- predilection of research and conditioning practicetionally, some research findings have been inter- on improving power may be misplaced. That is,preted erroneously and, as such, conclusions about strength qualities such as impulse, RFD or explosivepower development are questionable. For example, strength may better predict athletic performance andthe work of Schmidtbleicher and Buehrle[38] has hence it is the development of these qualities thatbeen used as justification for the use of high loads research and strength training should focus on. Fur-for the development of power.[9,15] However, this ther confounding the understanding of power as-study only measured the changes in maximum force sessment and development is the practical signifi-and RFD, and changes in these strength qualities are cance of mean and peak power output. The impor-not necessarily representative of changes in power. tance of these two variables, their relation toClearly, in each of these cases, different strength different athletic activities and their development iscapabilities are being investigated or discussed, each not well documented and for the most part poorlyrepresentative of different regions of the force-time understood. The first part of this section will critiquecurve as opposed to power the product of force and the literature that has investigated the relationshipvelocity. Each of these strength qualities conceiva- between power and athletic performance. Thereaf-bly needs to be developed in a different manner to ter, the relationship between other strength capabili-power. For example, the relationship between tradi- ties and athletic performance will be discussed in antional measures of force and power, and measures of effort to clarify the importance of Pmax in improvingexplosive strength (index of explosive strength, re- athletic performance.



3.1 Upper Body equally effective in explaining the shared variancebetween strength/power measures and the perform-

There is a paucity of data concerning the relation- ance measure. However, it should be noted that Pmaxship between power measures and upper-body func- was not determined in this study but rather thetional performance. This may be a result of the power outputs associated with a concentric-onlydifficulty of finding a suitable upper-body test that is bench-press throw (10kg) were calculated.as widely accepted as sprinting or jumping. Howev-er, tasks such as throwing shot-puts, balls or unload- 3.2 Lower Bodyed barbells have been used in the literature. Forexample, Mayhew and colleagues[41-43] have ex- In terms of the lower body, the manner in whichamined the relationship between bench-press power power has been calculated and the variety of exer-and shot-put throw in a number of studies. They cises used to assess power make comparisons be-found that bench-press power output using an abso- tween studies difficult (see table IV). As a result, thelute load of 20kg (~40% 1RM) was non-significant- importance of power as a determinant of athleticly correlated (r = 0.38) to seated shot-put throw for performance is difficult to disentangle. One ap-64 female college athletes.[42] For 40 college football proach to clarify the role of power as a predictor ofplayers, Mayhew et al.[41] found that the seated shot- athletic performance is to discuss power assessmentput throw was significantly correlated to bench- within certain frameworks noting thereafter whetherpress absolute power (r = 0.51) and relative power the literature supports such a contention.output (r = 0.66) assessed using a load of 60% 1RM.Mayhew et al.[43] also reported that none of the 3.2.1 Cyclic versus Acyclic Assessmentchanges in seated shot-put distance were significant- Theoretically, tests of power output that are cyc-ly correlated to increases in bench-press power out- lic in nature, involve the stretch-shorten cycle (SSC)put (loads 30–80% 1RM) at the conclusion of a and include horizontal as well as vertical motion12-week training study. It would seem that the should better predict performance in tasks such asstrength of the relationship between power output running and agility performance. The Margaria-and seated shot-put throw could possibly be influ- Kalamen step test is one of the more widely usedenced by the mass of the bench-press load, the mass tests used to calculate anaerobic power: power =of the shot-put, and the strength and sex of the (subject mass [kg] × 9.8 N/kg × 1.02 [vertical dis-subjects. tance between test stairs])/time taken to ascend test

Baker[31] found that Pmax was significantly relat- stairs. Significant correlations (r = –0.43 to –0.71)ed (r = 0.46) to an incline bench-press throw (20kg), were reported between power and sprint and agilityan exercise deemed to indicate upper-body speed performance using this test, only when power outputcapabilities. Pmax explained only 21% of the vari- was expressed relative to mass (see Mayhew etance associated with the so-called functional per- al.,[42] table II). The highest correlation was reportedformance measure. It also should be noted that pow- between the 36.5m (40-yard) dash time and the steper outputs associated with absolute loads of 40 and test. This makes sense as theoretically the greater the60kg were significantly related to the performance approach velocity during the test, the greater themeasures (r = 0.42–0.50). Cronin and Owen[44] in- vertical velocity and, therefore, power output. How-vestigated whether chest-pass distance was related ever, there is still a great deal of unexplained vari-to various strength and power measures of the upper ance (50–81%) between the step test and the mea-body as measured by a bench-press throw (10kg) on sures of performance. Some studies have reporteda Smith machine. A significant relationship between that approach velocity and power output are onlymaximal strength (r = 0.71), mean power (r = 0.77), moderately correlated[50] and, therefore, it has beenpeak power (r = 0.80) and impulse (r = 0.81) and the speculated that something more than vertical veloc-chest pass were reported. It seems that impulse is ity accounts for power production. The shared vari-


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Table IV. Relationship between measures of power and performance for the lower body

Study Subjects Power measure Performance measure r

Baker and Nance[45] 20 professional rugby Loaded jump-squats across loads of 10m sprint time –0.02 to –0.08 (NS)league players 40, 60, 80 and 100kg 40m sprint time –0.52 to –0.61*

Absolute (W) –0.02 to –0.17 (NS)Relative (W/kg) –0.52 to –0.76*

Chelly and Denis[46] 11 M handball players Average hopping power Maximal track running velocity 0.66*Average treadmill power (W/kg) 0.20 (NS)Average treadmill power 0.73*

Driss et al.[47] 18 M volleyball players Anaerobic power (Pmax) on cycle Vertical Jump 0.75**(6 sec) expressed as W/kg

Kukolj et al.[48] 24 well conditioned M PE Average leg power per kg of body 0–15m time 0.03 (NS)students mass from continuous jumping 15–30m time 0.26 (NS)

protocol according to Bosco et al.[49]

Mayhew et al.[50] 53 football players Anaerobic power (W) 9m (10yd) dash time 0.16 (NS)Anaerobic power (W/kg) 36.5m (40yd) dash time –065*Margaria-Kalamen step test Agility – modified Missouri State 0.21 (NS)

agility run –071*0.22 (NS)–0.43*

Meckel et al.[51] 20 F track athletes Wingate anaerobic test (30 sec): 100m sprint from standing start –0.8810 recreationally trained F maximum power (W/kg)

Nesser et al.[52] 20 sportsmen Wingate 10 sec anaerobic test: 40m sprint time –0.46*anaerobic power (W/kg)

Sleivert and 30 M rugby league, rugby, Split squat 5m time MP: –0.68**Taingahue[25] and basketball players Traditional squat 5m time PP: –0.65**

MP: –0.64**PP: –0.66**

Thomas et al.[30] 19 untrained F Double leg-press peak power output Vertical jump 0.73 (p < 0.004)Sprint 36.5m (40yd) 0.14 (p < 0.573)

Young et al.[53] 18 footballers CMJ (power) 20m straight sprint 0.66 (NS)4 × 20m sprints bouncing football orchanging direction (agility)

CMJ = counter-movement jump; F = females; M = males; MP = mean power; NS = not significant; PE = physical education; Pmax = maximal power output; PP = peak power; * p <0.05; ** p < 0.001.


ance between the power and performance measures Nance[45] with the absolute power values being thewould certainly support such a contention. only measures significantly related to maximal ve-

locity in a 40m sprint. Both studies investigated theOther studies that have used cyclic SSC assess-relationship between power output and sprint timesment include Chelly and Denis[46] who used a tread-of athletes over fairly similar distances, the differ-mill sprint test and Kukolj et al.[48] who used contin-ences in dynamometry (jump-squats vs treadmilluous jumping protocol. The best single predictor ofsprints) being the major difference between studies.maximal running velocity was treadmill forward legIt should be pointed out that in the study of Chelleypower (r = 0.73) in Chelly’s study; however, thisand Denis,[46] although relative power was not corre-only accounted for 53% of the variance. Kukolj etlated to maximal running velocity, it was stronglyal.[48] found no significant relationship between theircorrelated to sprint acceleration (r = 0.80). Of thepower measures and sprint times.other studies that expressed power output relative toAnother test of anaerobic power that is cyclic inbody mass, the results were mixed with high,[51]nature but does not involve SSC motion is the Win-moderate,[47] low[52] or non-significant relation-gate cycle test. Three studies[47,51,52] used the powerships[48] to measures of performance reported. Thereoutput from the Wingate test to predict jump andappears to be no clear consensus as to the impor-sprint performance. Once more the diversity in test-tance of normalising power output to body mass foring procedures is apparent, even when the same testpredicting performance. Also, most normalisedis used. All three studies calculated power outputpower outputs (the exception being Meckel et al.[51])over different time periods. Furthermore Driss etexplained <57% of the common variance associatedal.[47] determined Pmax and used this measure forwith the performance measure. Meckel et al.[51]comparisons, Nesser et al.[52] used peak power dur-studied a very large group (n = 30) of mixed sprinting their 10-second work bout and Meckel et al.[51]

ability (mean 100m time ranged from 11.1 secondsused the highest work performed during any 5-sec-in the fastest group [n = 10] to 14.2 seconds in theond work interval. The variety in outcome measuresslowest group [n = 10]). Heterogeneity of subjectsbetween studies also makes comparisons difficultmay have contributed to the high correlations report-and it is no wonder a wide range of correlationsed.between power and performance measures were re-

ported (r = –0.46 to –0.88). From the studies repre-3.2.3 Maximum Power versus Power Outputsented in table IV it appears that the power outputsThe low shared variance between power outputassociated with cyclic type motion do not predict

and performance measures reported previously mayperformance any better than acyclic measures.be due to the fact that most of the studies have not

3.2.2 Absolute versus Relative Power Output determined Pmax for the assessment that is predict-It may be that power needs to be normalised to ing the performance measure. Baker and Nance[45]

body mass for power output to be truly representa- reported that Pmax/kg was significantly related totive of the power needed to run and jump. Once 10m (r = –0.56) and 40m (r = –0.76) sprint perform-more, the literature is confusing. Two studies[45,46] ance. However, the strength of these correlationshave represented their power outputs in absolute were very similar to the correlations associated with(W) and relative (W/kg) terms. The absolute power other loads and in the case of 10m sprint perform-outputs of Baker and Nance[45] were not significant- ance, the correlations between Pmax and speed werely related to 10 or 40m sprint performance; however, lower than the correlations reported for some of thewhen expressed relative to body mass, significant other loads. Driss et al.[47] also determined Pmax for arelationships were reported (r = –0.52 to –0.76), 6-second sprint test on a cycle at different brakinglikely because body mass must be accelerated in forces. The braking force that maximised Pmax wassprinting. However, some of the findings of Chelly recorded and related to functional performance (ver-and Denis[46] are the antithesis of Baker and tical jump). Unlike Baker and Nance,[45] the other



power outputs associated with various loads and measured. Reviewing research that has investigatedsubsequent relationships were not reported in this the ability of a variety of strength and power mea-study, therefore, conclusions cannot be made as to sures to predict athletic performance, may give bet-the significance of the load that optimises Pmax in ter insight into the importance of power as a deter-relation to other loads. In both studies, however, minant of athletic success.Pmax accounted for <58% of the shared variance Cronin et al.[40] assessed the strength, power andbetween the performance measures. explosive strength of the leg musculature on a su-

It appears that none of these frameworks clarify pine squat and related these measures to lunge per-the importance of power output or Pmax as predic- formance (lunge foot contact times: 0.354 sec +tors of performance more so than the other. Given 0.063). The only significant strength predictors ofthe great variety of assessment techniques, it might lunge performance were all explosive strength mea-have been expected that one type of assessment may sures (index of explosive strength [r = 0.62], reactiv-predict performance to better effect. This was not ity coefficient [r = 0.61], starting gradient [r = 0.69]the case, the greatest shared variance between a and acceleration gradient [r = 0.59]). Maximalmeasure of power and performance being 77% and strength, mean and peak power were not significant-most coefficients of determinations approximately ly related to performance of this movement.[40] In50% or less. It may be that power is not an important another study, Sleivert and Taingahue[25] investigat-determinant of performance and other strength mea- ed the relationship between sprint start performancesures may be of equal or greater importance or (5m sprint time) and strength and power variablespower measurements have not be appropriate for the determined from concentric jump-squats in 30 maleperformance. athletes. Both average and peak power expressed

relative to body mass were significantly related toIt has been suggested that for activities that re-5m sprint time (r = –0.64 to –0.68). Force (r = 0.59)quire fast force production (100–300ms) such asand bar velocity (r = 0.40) were also significantlythrowing, jumping and sprinting,[6] that the rate atrelated to 5m sprint time. However, with the excep-which force is developed is the most importanttion of peak force, these relationships were muchdeterminant of athletic success.[54] Wilson et al.[55]

less substantial than those demonstrated for averageinvestigated the relationship of a series of isometric,and peak power. During the sprint start, the bodyconcentric and SSC rate of force development testshad to be accelerated rapidly from stationary and theperformed in an upright squat position to sprintingpropulsive impulse was large, so there may haveperformance. Of the 20 force-time variables gener-been a greater reliance on high force production asated using a modified Smith machine over a forceopposed to high movement velocity.platform, the concentric force at 30ms was the only

measure significantly correlated to sprint perform- Young et al.[56] using a similar methodology toance (r = –0.616) and, in addition to concentric Wilson et al.[55] investigated the relationship be-maximum RFD, were the only measures able to tween 27 strength and power measures and theeffectively discriminate between good and poor per- sprinting performance of 20 elite junior track andformers.[55] The authors emphasise the superiority of field athletes (11 males and 9 females). There wasconcentric RFD tests over and above isometric and no mention whether the pooling of the male andSSC RFD tests and suggest their inclusion in sport female subjects were investigated for bipolar distri-science test batteries. It should be remembered, bution (by sex), which can result in artificially highhowever, that concentric RFD and force at 30ms correlations. Therefore, the magnitude of the corre-explained <38% of the variance associated with 30m lations need to be interpreted with caution. Youngsprint performance. Furthermore, this type of meth- and colleagues[56] assessed vertical jumping move-odology does not clarify whether power is a better ments utilising purely concentric, SSC and isometricpredictor of athletic performance, as power was not contractions performed over a force platform, found



that concentric strength measures were the best into all the mechanisms responsible for performancepredictors of sprint performance. The best predictors of a task. Secondly, other factors such as strengthof starting performance (time to 2.5m) were all measures, body mass, flexibility and leg length willobtained from a concentric-only jump-squat and have diverse effects on the statistical models. Basedincluded three force measures (maximum dynamic on these results, it is suggested that the sports train-strength/weight [r = –0.86], force in 100 ms/weight er, sport scientist or clinician should not rely solely[r = –0.73], maximum force [r = –0.72] and one on a single power measurement to predict perform-power measure (average power/weight [r = –0.74]). ance or readiness to return to activity after injury.The single best predictors of maximum sprinting Rather, research needs to determine the influence ofspeed were the force relative to bodyweight generat- these other factors on athletic performance. It mayed after 100ms from the start of the concentric jump be that several factors in combination with powermovement (r = –0.80) and maximum force (r = measures will provide the best predictive capabili-–0.79). Average power relative to bodyweight was ties of functional performance. Therefore, the chal-also strongly related to maximum velocity (r = lenge is to develop assessment batteries that provide–0.79). Together, the findings of these studies sug- insights into the key mechanisms responsible for thegest that for many types of activities, various rates of performance of a task. It must also be rememberedforce development and maximal force measures that a significant relationship to performance doesmay be as predictive of performance as measures of not imply that a particular strength or power attri-maximal power. The magnitude of these relation- bute, when loaded during training, will enhanceships appear to depend upon the kinetics and kine- performance. Only longitudinal data from trainingmatics of the performance in question, and specifici- studies can provide information regarding optimalty of neuromuscular demand appears to be a critical training methods, if indeed optimal methods exist.factor in determining the strength or power attribute

4. Power and Performance:that best predicts performance. It should be remem-Training Studiesbered, however, that just because a strength or pow-

er attribute is related to performance, that does notResearch that has investigated the developmentnecessarily indicate that training that particular attri-

of power is typified by a great deal of variation inbute will enhance performance.the methodological approaches used. The scope ofthis variation makes comparisons difficult and3.2.4 Summaryhence definitive conclusions practically impossible.Implicit in the small number of meaningful corre-For example, the vast majority of research has beenlations and large amount of unexplained variance inrelatively short in duration (8–12 weeks) and, there-the data of table IV is that sport scientists need tofore, the application of findings to long-term train-formulate better methods, models and theories toing is questionable as the influence of neural andcontribute significantly to knowledge that is usefulmorphological mechanisms change with trainingto athletes and their coaches in terms of power andduration.[57] Research in this area is also typified byperformance. It has been suggested that sport scien-a wide spectrum of loading parameters that includetists adopt a specific functional term to denote thedifferences in:ability to perform high-velocity explosive force-• volumegenerating movements and limit the term ‘power’ to• intensity (% 1RM)its correct usage as defined by Newtonian mechan-• total work outputics.[36] Whether this is necessary is debatable. It may• tempo of concentric-eccentric contractionsbe that the preoccupation of correlational studies to• frequencyfind the best power predictors of functional perform-• rest/recovery time – densityance is fundamentally flawed. First, one power mea-

sure cannot adequately express or provide insight • type of contractions.



Further confounding our understanding in this with plyometric training on a variety of performancearea are the modes of dynamometry used and variety measures. Conversely Komi et al.[61] compared theof strength power measures reported. These issues effect of heavy-load training versus light-load train-have been discussed in section 3. Finally, many ing combined with explosive jump training on vari-different muscle groups have been studied, limiting ous performance measures. Any performancethe ability to generalise results, especially in the case changes, however, cannot be attributed to a loadof uni- and bi-articular muscles. To discuss each of effect as one treatment group has incorporated addi-these limitations is outside the scope of this article. tional plyometric training. Unfortunately this type ofHowever, a brief mention will be made of some methodology is not uncommon and as such does notissues that are thought influential to subsequent dis- offer insight into specific loading intensities thatcussion. affect power and performance.

First, a clear understanding of each research Further confounding our understanding of themethodology needs to be realised, so as the interpre- effects of resistance training on the development oftation and application of their findings are not mis- power is the preponderance of research using novicerepresented. For example, the study of Schmidt- weight trainers or students as subjects (see table V).bleicher and Buerhle[38] compared the effects of This is due to the accessibility of such subjects tothree types of training regimes (maximum load researchers. Novice subjects and/or student popula-[90–100% maximal voluntary contraction, MVC], tions are generally easy to access and it is easy topower load [45% MVC] and hypertrophy load [70% have a control group in such designs. However, it isMVC]) on various neuromechanical and morpho- more problematic to find a suitable cohort of sub-logical variables. In terms of tracking these changes, jects from an athletic population and practicallyan isolated isometric elbow extension movement impossible to ask a group of athletes to cease train-was used. Consequently, power was not assessed as ing and act as controls. Nonetheless, it has beenno movement took place. Furthermore, isometric shown that novices respond in a generic manner to aand dynamic contractions have been shown to differ very broad range of resistance training stimuli.[62,63]

in terms of their physiology and neuromechanics.[58] Thus, the validity of generalising findings from nov-Similarly, the findings of Hakkinen et al.[59] are used ice subjects to athletes with experience in weightto support the use of light-load explosive jump train- training needs to be done so with caution as theing for power development. However, there were no findings may in fact be compromised by theother training or control groups cited in this paper trainability of the novice subjects.and the changes in performance from the 24 weeks Volume is commonly expressed as the total prod-of training were tracked by measuring isometric uct of repetitions, sets and load (% 1RM). Equatingforce and various force-time parameters. These arti- by volume is the most common method by whichcles, however, are often quoted in power training research compares the effect of load on variousliterature even though power has not been measured. outcome measures. Alternative methods includeThe application of such findings for improving the equating with total time under tension as measuredpower of multi-articular dynamic motion would ap- by electromyographic (EMG) activity or totalpear problematic on a number of counts. mechanical work performed.[67] A great deal of re-

Another common methodological problem when search has failed to equate loading between trainingstudying the effect of load is that authors combine protocols in any form[38,65,69,70] and, as a result, thetraining methods, which make the effects of the findings of such research must also be interpretedindependent variable impossible to disentangle. For with caution especially if the effect of load is beingexample, Lyttle et al.[60] investigated the effects of investigated. For example, Harris et al.[65] studiedmaximal power training (30% 1RM) versus heavy- the effects of different training protocols on wellload training (6–10RM or 75–83% 1RM) combined trained subjects. One group used heavy-load squats



Table V. Studies that have examined the effect of load on power output and performance

Study Subjects Training loads used Power and performance measures

Cronin et al.[64] 21 F provincial netball players (1) 60% 1RM Mean and peak powerwith no recent weight-training (2) 80% 1RM Netball throw velocityexperience (3) Control

Equivolume training for 10wk

Harris et al.[65] 51 university football players (1) 30% 1RM Average VJ powerwith at least 1y of weight- (2) 80% 1RM Peak VJ powertraining experience (3) Com 30% and 80% 1RM Standing long jump

Not equivolume – 13wk MK step testAgility test30m sprint

McBride et al.[66] 26 athletic men with 2–4y (1) 30% 1RM Peak powerstrength-training experience (2) 80% 1RM 20m sprint time

(3) Control Agility T-testEquivolume training for 8wk

Moss et al.[67] 31 well trained PE students (1) 15% 1RM Power-load spectrum(2) 35% 1RM(3) 90% 1RMEquivolume training for 9wk

Scmidtbleicher and 30 M PE students (1) 30% MVC No power measuresHaralambie[68] (2) 90–100% MVC Maximal speed of push-off movement

(3) ControlEquivolume training for 8wk

Schmidtbleicher and 59 M students (1) 45% MVC No power measuresBuehrle[38] (2) 70% MVC No performance measures

(3) 90–100% MVCNot equivolume – 12wk

Wilson et al.[69] 64 subjects with 1y weight- (1) 30% 1RM No measures of powertraining experience (2) 6–10RM = 75–83% 1RM JS Ht

(3) Plyometric CMJ Ht(4) Control Sprint and cycle testsNot equivolume – 10wk

1RM = one repetition maximum; CMJ = counter-movement jump; Com = combined training; F = females; Ht = height; JS = jump-squat; M =males; MK = Margaria-Kalamen step test; MVC = maximal voluntary contraction; PE = physical education; VJ = vertical jump.

of 80–85% 1RM (high force [HF]), one with lighter standing long jump, significantly greater increasesin the HP (3.45%) group than COM (1.63%) or HFload squats of approximately 30% 1RM (high power(1.29%) groups were observed. These differential[HP]), and one with a combination (COM) of train-training effects are interesting; however, it may being methods. Subjects were instructed to perform allthat the noted training effects were not due to thelifts as explosively as possible although not actuallydifferent kinematics and kinetics characteristics ofjump. Pre- and post-training tests included: 1RMthe various training protocols, but rather the differ-squat, 1RM one-quarter squat, 1RM mid-thigh pullent training volumes of each group.and various tests of speed and jump height. After 9

weeks of training it was observed that performance Wilson et al.[69] is an often-quoted study thatchanges reflected contraction force specificity. That experiences the same problem. These researchersis, the COM and HF groups increased 1RM strength examined the effects of three different trainingsignificantly more than the HP group (24.7%, 21.9% modes on strength and power outputs over theand 9.6% for COM and HF and HP, respectively, course of 10 weeks of training. Previously trainedaverage increase across squat and one-quarter squat subjects were divided into three subject groups. One1RM). However, for some low-force, high-velocity trained with traditional ‘heavy’ (6–10RM) squatsmeasures of functional performance such as the (TR), one with jump-squats at Pmax (around 30% of



maximum isometric force [MP]) and one with ply- listic’ strength training[35] and is thought superior totraditional strength-training methods as the velocityometric unloaded depth jumps (0.2–0.8m [PL]).and acceleration/deceleration profiles better approx-Tests before and after the training period includedimate the explosive movements used in athletic per-sprint time, vertical jump height and peak power in aformance.[21,32]6-second cycle test. The results indicated that the

MP training group demonstrated the best overall Careful consideration also needs to be given toimprovements in functional performance. Increases the type of isoinertial assessment used in trainingin countermovement jumps (17.6%) and jump- studies, as assessments must balance between beingsquats (15.2%) were significantly greater than the specific to the functional task whilst being suffi-TR (4.8% and 6.3%) and PL (10.3% and 6.5%) ciently different from training so that it does notgroups. They concluded after a training study that advantage one of the training groups. For example,compared heavy weight training (6–10RM), ply- it can reasonably be expected that a group trainingometric training (drop jumps from 0.2–0.8m) and with heavy loads would achieve greater improve-maximum power training (30% 1RM) that the Pmax ments in 1RM than a group training with lightertraining produced the best overall results.[69] Once loads. Therefore, assessments should either includemore, intensity and volume have not been equated tests across a range of loads or at a ‘neutral’ load thatand, therefore, it is impossible to disentangle the will not bias the results for any particular group.training effects. That is, the results from such studies

Finally, all the papers cited in table V experienceare difficult to interpret as the reported differencesa basic but fundamental problem if the effect ofbetween various training protocols may in fact betraining at Pmax is to be established. No paper hascontaminated by differences in training volume,established Pmax for their respective subjects, therather than the specific kinematic and kinetic char-training load selected has been based on previousacteristics of the different loading intensities. Mak-research. The perils of such an approach have beening conclusions about the efficacy and/or adapta-discussed throughout this paper with many findingstions of various training protocols that are not equat-such as Edgerton et al.,[11] Faulkner et al.,[12] Kanekoed in some manner would appear highlyet al.,[13] Schmidtbleicher and Buehrle,[38] misinter-questionable.preted and/or misrepresented. The dangers of such

Further complicating our understanding in this an approach are further reinforced if tables I and IIarea is that changes in performance may be related are observed, that is which load (% 1RM) should beto the movement pattern used rather than differences used as Pmax for a training study. If the effects ofin loading intensity. For example, in the Wilson et Pmax training are to be understood, Pmax needs to beal.[69] article, it may be that the superior performance determined specific to the population and trainingof the maximum power groups was not due to train- exercise used. The power loads selected for studying at the ‘optimal load’ but rather that jump-squat have mostly been based on research (e.g. Kaneko ettraining (ballistic training) offers greater movement al.[13]) that cites the superiority of lighter loadspattern specificity than more traditional strength- (30–45% 1RM). Tables I and II and previous discus-training methods. Traditional strength-training tech- sions of research such as that of Kaneko et al.[13]

niques in which a bar is held at the completion of the would suggest that this is not advisable practice.motion have been criticised due to large decelera- Only one study[64] based their selection of Pmax ontions during the concentric phase, proportional to their own previous research using similar athletesthe load and, therefore, velocity of movement.[32,71] and assessment equipment to their original re-Strength training that allows the projection of the search.[16] In this study, the effects of heavy-loadload avoids this problem by allowing the athlete to training (80% 1RM) and maximum power training

(60% 1RM) on the power and chest-pass perform-accelerate the bar throughout a greater range ofance of semi-elite netball players were compared.movement. Such training has been described as ‘bal-



Significantly greater mean and peak power outputs three groups at loads ≤50% 1RM but for the higherloads (70% and 90% 1RM) the increase was signifi-(40% 1RM bench-press throw) were observed forcantly larger for G90 and G35 compared with G15.the heavy-load group; however, no significant dif-In essence, the findings illustrate loads of 35% andferences in chest-pass throw velocity between train-90% 1RM were equally effective in improving pow-ing groups were found. However, it should be noteder output across a spectrum of loads.that the players had little or no weight-training expe-

rience. Another study investigating the effects of heavy-(80% 1RM) versus light-load (30% 1RM) trainingThe types of problems described in this sectionon strength, power and speed in experienced weightare symptomatic of research in this area, the readertrainers was conducted by McBride et al.[66] Jump-having to be discerning in their choice of literaturesquats were used for both training and testing, andto shape their knowledge and practice. To gain a truegroups were equated for volume using sets × repeti-appreciation of the effect of load on power develop-tions × load (%RM). After 8 weeks of training, bothment, research methodologies need to equate thegroups increased 1RM significantly (10.17% andload lifted in some manner. Ideally, well trained8.23% for 80% 1RM and 30% 1RM groups, respec-subjects should be trained at different loads (%tively) with no significant difference between1RM), the effects of which need to be reported asgroups. Similarly, there were no significant be-changes in mean and/or peak power and/or changestween-group differences in peak force, peak powerin functional performance. Unfortunately, the num-or jump height pre- and post-training. Of the threeber of studies that have adopted such an approachsprint (5, 10 and 20m sprint time) and agility (T-testare few (see table V) and, as mentioned previously,time) measures, the 30% 1RM training proved supe-none of these studies determined or trained at Pmax.rior to 80% 1RM training on only one measure (10mTherefore, the importance of Pmax remains a mys-sprint time). The results of these two studies suggesttery. Nonetheless, two studies seem to have resolvedthat there is very little difference in the effects ofsome of the limitations highlighted in previous sec-heavy- and light-load training in terms of power andtions and may offer insights into optimising the loadperformance.selected during resistance training strategies to de-

velop maximal power and enhance performance. The lack of a differential training effect in thesestudies using quite different loads may be explainedMoss et al.[67] had three groups of subjects trainif training velocity and actual movement velocity ofthe elbow flexors of the non-dominant arm while thea task are compared. For example, the velocitiesdominant arm served as a control. The three groupsattained during a concentric-only bench-press throwtrained at 90% 1RM for two repetitions (G90), atand a rebound bench-press throw on a modified35% 1RM for seven repetitions (G35) and at 15%Smith-Press machine can be observed from figure1RM for 15 repetitions (G15), respectively. All1.[64] Such motion has been reported to more closelygroups trained with three to five sets and weresimulate the velocity and acceleration profiles asso-equated for total time under tension based on EMGciated with throwing.[32] The velocity profiles ob-activity (muscle activation). Subjects were en-tained from these 27 male athletes are similar tocouraged to perform each lift as fast as possible, butthose recorded in other research of this kind.[9,32]

the weight was held rather than projected. Measure-ments before and after the study included 1RM and For sports-specific motion that uses muscles sim-various force and power outputs. Power was tested ilar to the bench press the comparison of actualacross a range of loads from 2.5kg to 90% 1RM and movement velocity to training velocity make forincreased for all loads tested in G90 and G35. An interesting analysis. Ritzdorf[72] details release ve-increase in a lighter range of loads from 15% to 50% locities of 13 m/sec for the shot-put motion. Average1RM was observed for G15. The increases in power release velocities of 11.98 m/sec for the chest passoutput were not significantly different between the of semi-elite female netball players have also been



0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

30 40 50 60 70 80

Percentage 1RM

Ave

rage

vel

ocity

(m

/sec

)Concentric bench-press throwRebound bench-press throw

Fig. 1. Average velocities and standard deviations associated with the concentric bench-press throw and the rebound bench-press throwover a range of loading intensities (30–80% one repetition maximum [1RM]).

reported.[64] Furthermore, other studies (as reported rapidly develop force. This assertion must be inter-by Ritzdorf[72]) have reported that the segment ve- preted cautiously as Schmidtbleicher and Buehrle[38]

locities (shoulder, elbow and hand) combined to found the greatest improvements in RFD resultedproduce racquet head velocities of approximately 30 from maximum load training (90–100% MVC) asm/sec for the tennis serve. It would seem that there opposed to maximum power (45% MVC) trainingare clear differences between the velocities associat- (34% and 11% improvements, respectively). Ited with the most common strength-training loading should be remembered that rate of force develop-intensities (30–80% 1RM) and the actual movement ment can be independent of external movement ve-velocity of a sport-specific task. There is no doubt locity. In addition, maximal rate of force develop-that resistance strength training can improve func- ment and motor unit activation in a maximum efforttional performance. However, the importance of contraction is relatively constant for an individualload in terms of velocity specificity would appear and is generally not influenced by the external loadquestionable, due to the disparity between the actual or speed of movement.[73] In Schmidtbleicher andmovement velocities of most athletic tasks and the Buehrle’s study[38] both groups were instructed totraining velocities achieved during weight training. develop their contractions as fast as possible. It mayIt may be that load is not as important as many think be that irrespective of load and limb velocity, theand other factors may be more important to better repeated intent to move ‘explosively’ is the impor-develop and explain improvement to functional per- tant stimulus for muscular adaptation. The findingsformance. For example, as suggested in section 3, it of Behm and Sale[74] support such a notion, as theymay be that rate of force development rather than found that regardless of the actual velocity of move-power output is a more important determinant of ment (isometric versus isokinetic), it was the inten-athletic success. Newton and Kraemer[35] stated that tion to execute a high-velocity movement, whichheavy loading (70–120% 1RM) does not improve resulted in high-velocity adaptation and substantialthe maximum rate of force development, rather ex- increases (26%) in rate of force development. Alongercises such as explosive jump training using resis- these lines, it has been recently shown with surfacetances of 30–60% 1RM best increase the ability to electromyography, that at loads between 30–80%



1RM, power, force and velocity values differ, but ance to better effect and direct assessment and con-muscular activation is similar during maximal effort ditioning practice in a more efficient and systematicballistic jump-squats.[19] Thus, when the intent to fashion.move is maximal, any differences in training effects If Pmax is found to be important, then each indi-due to loading differences are likely due to differ- vidual’s Pmax needs to be determined and they thenences in the mechanical stimuli at the muscle, not train at this load. The predilection of research toactivation differences. train all subjects at one load (e.g. 30% 1RM) is

fundamentally flawed due to inter-individual Pmaxdifferences, which may be ascribed to factors such5. Conclusionsas training status (strength level) and the exercise

Many problems have been magnified throughout (muscle groups) used. Pmax needs to be constantlythis article that currently exist within this field of monitored and adjusted as research suggests that it isstudy. From the use of fundamental definitions and transient. In terms of training studies, experiencedterminology to training studies, the literature ap- subjects should be used, volume equated and thepears hewn with confusion and methodological outcome measures clearly defined and measuredproblems. It is hoped that this article has eliminated (i.e. mean power and/or peak power).some of this confusion and clarified the type of Until training studies address the limitations dis-research needed if we are to advance our knowledge cussed throughout this paper, the best and safestand practice on the importance of maximising power course of action for those interested in improvingoutput and its transference to athletic performance. the power output of muscle may be to use a mixedSport scientists are urged to formulate research de- training strategy using both heavy and light loads.signs that result in meaningful and practical infor- Realising that all human movement is an integrationmation that assists coaches and strength and condi- of force and velocity, such an approach is intuitivelytioning practitioners in the development of their appealing. That is, most sports involve a mixture ofathletes. activities that span the force-velocity capability of

In summary, it is apparent there is a need for a muscle. For example, the shot-putter has to drivegreat deal more research on the importance of train- their quite sizeable mass through the circle beforeing at Pmax and whether it advantages athletic per- throwing a relatively light shot-put. Rugby playersformance over and above other loading intensities. not only have to wrestle and tackle each other butFirst, the importance of Pmax to athletic performance also kick and throw a ball. Intuitively, it would seemneeds to be established. It must be remembered that prudent to continuously adjust the resistances usedpower is only one aspect that affects performance for power training, as athletic performance is typi-and it is quite likely that other strength measures fied by many force-velocity characteristics. Further-may be equally if not more important for determin- more, as one of the principles of training is variationing the success of certain tasks. The coach and/or (periodisation) this approach would seem most logi-sport scientist must be aware of this and identify cal.those strength qualities that are critical determinants

Acknowledgementsof their athletic activity and thereafter devise appro-priate assessment strategies and training program- No sources of funding were used to assist in the prepara-mes so as these determinants are improved in a tion of this review. The authors have no conflicts of interestsystematic fashion. It is suggested that instead of that are directly relevant to the content of this review.

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