Peak power output (PPO) during cycling is the maximum power output over a single crank revolution during a short (usually <10-s) period of time. 1 , 2 The PPO during cycling in a laboratory environment can be accurately measured and is comparable to maximal sprints on the track. 3 Specifically
Mehdi Kordi, Martin Evans, and Glyn Howatson
Amândio M.C. Santos, Joanne R. Welsman, Mark B.A. De Ste Croix, and Neil Armstrong
Age- and sex-related differences in optimal peak power (PPopt) and associated measures determined using a force-velocity (F-V) cycling test were examined in pre teenage, teenage and adult males and females. Absolute PPopt increased significantly with age in both males and females. With body mass controlled for using allometric scaling significant age related increases remained, an effect masked in the females when PPopt was expressed as W • kg−1. Sex differences in PPopt were minimal in the preteens but males demonstrated higher PPopt than females in both teenage and adult groups. These patterns of change with age and sex broadly reflect those obtained for Wingate Anaerobic Test determined PP but the use of a single non-optimized braking force underestimates the magnitude of any differences observed.
Andrea Monte, Francesca Nardello, and Paola Zamparo
The effects of different loads on kinematic and kinetic variables during sled towing were investigated with the aim to identify the optimal overload for this specific sprint training.
Thirteen male sprinters (100-m personal best: 10.91 ± 0.14 s) performed 5 maximal trials over a 20-m distance in the following conditions: unloaded and with loads from 15% to 40% of the athlete’s body mass (BM). In these calculations the sled mass and friction were taken into account. Contact and flight times, stride length, horizontal hip velocity (vh), and relative angles of hip, knee, and ankle (at touchdown and takeoff) were measured step by step. In addition, the horizontal force (Fh) and power (Ph) and maximal force (Fh0) and power (Ph0) were calculated.
vh, flight time, and step length decreased while contact time increased with increasing load (P < .001). These variables changed significantly also as a function of the step number (P < .01), except between the 2 last steps. No differences were observed in Fh among loads, but Fh was larger in sled towing than in unloaded. Ph was unaffected by load up to +20%BM but decreased with larger loads. Fh0 and Ph0 were achieved at 20%BM. Up to 20%BM, no significant effects on joint angles were observed at touchdown and takeoff, while at loads >30%BM joint angles tended to decrease.
The 20%BM condition represents the optimal overload for peak power production—at this load sprinters reach their highest power without significant changes in their running technique (eg, joint angles).
Michael J. Duncan, Joanne Hankey, and Alan M. Nevill
This study examined the efficacy of peak-power estimation equations in children using force platform data and determined whether allometric modeling offers a sounder alternative to estimating peak power in pediatric samples. Ninety one boys and girls aged 12–16 years performed 3 countermovement jumps (CMJ) on a force platform. Estimated peak power (PPest) was determined using the Harman et al., Sayers SJ, Sayers CMJ, and Canavan and Vescovi equations. All 4 equations were associated with actual peak power (r = 0.893−0.909, all p < .01). There were significant differences between PPest using the Harman et al., Sayers SJ, and Sayers CMJ equations (p < .05) and actual peak power (PPactual). ANCOVA also indicated sex and age effect for PPactual (p < .01). Following a random two-thirds to one-third split of participants, an additive linear model (p = .0001) predicted PPactual (adjusted R 2 = .866) from body mass and CMJ height in the two-thirds split (n = 60). An allometric model using CMJ height, body mass, and age was then developed with this sample, which predicted 88.8% of the variance in PPactual (p < .0001, adjusted R 2 = .888). The regression equations were cross-validated using the one-third split sample (n = 31), evidencing a significant positive relationship (r = .910, p = .001) and no significant difference (p = .151) between PPactual and PPest using this equation. The allometric and linear models determined from this study provide accurate models to estimate peak power in children.
Liam P. Kilduff, Huw Bevan, Nick Owen, Mike I.C. Kingsley, Paul Bunce, Mark Bennett, and Dan Cunningham
The ability to develop high levels of muscle power is considered an essential component of success in many sporting activities; however, the optimal load for the development of peak power during training remains controversial. The aim of the present study was to determine the optimal load required to observe peak power output (PPO) during the hang power clean in professional rugby players.
Twelve professional rugby players performed hang power cleans on a portable force platform at loads of 30%, 40%, 50%, 60%, 70%, 80%, and 90% of their predetermined 1-repetition maximum (1-RM) in a randomized and balanced order.
Relative load had a significant effect on power output, with peak values being obtained at 80% of the subjects’ 1-RM (4466 ± 477 W; P < .001). There was no significant difference, however, between the power outputs at 50%, 60%, 70%, or 90% 1-RM compared with 80% 1-RM. Peak force was produced at 90% 1-RM with relative load having a significant effect on this variable; however, relative load had no effect on peak rate of force development or velocity during the hang power clean.
The authors conclude that relative load has a significant effect on PPO during the hang power clean: Although PPO was obtained at 80% 1-RM, there was no significant difference between the loads ranging from 40% to 90% 1-RM. Individual determination of the optimal load for PPO is necessary in order to enhance individual training effects.
Amândio M.C. Santos, Neil Armstrong, Mark B. A. De Ste Croix, Peter Sharpe, and Joanne R. Welsman
These studies used multilevel modelling to examine optimised peak power (PPopt) from a force velocity test over the age range 12–14 years. In the first study, body mass, stature, triceps and subscapular skinfold thicknesses of boys and girls, aged 12.3 ± 0.3 y at the onset of the study, were measured on four occasions at 6 monthly intervals. The analysis was founded on 146 PPopt determinations (79 from boys and 67 from girls). Body mass and stature were significant explanatory variables with sum of two skinfolds exerting an additional effect. No gender differences were evident but PPopt increased with age. In the second study, thigh muscle volume (TMV) was estimated using magnetic resonance imaging at test occasions two and four. The analysis, founded on a subsample of 67 PPopt determinations (39 from boys and 28 from girls), demonstrated TMV to be a significant additional explanatory variable alongside body mass and stature with neither age nor gender making a significant contribution to PPopt. Together the studies demonstrate the influence of body size and TMV on young people’s PPopt.
Jorge Zuniga, Terry J. Housh, Michelle Mielke, Clayton L. Camic, C. Russell Hendrix, Glen O. Johnson, Dona J. Housh, and Richard J. Schmidt
The purpose of this study was to cross-validate the fat-free weight (FFW) equations derived on nonathletic children and adolescents for estimating mean power (MP) and peak power (PP) in high school wrestlers. One hundred and three male high school wrestlers performed the Wingate Anaerobic Test to estimate MP and PP, as well as underwater weighing to determine FFW. The follow equations were used to estimate the MP and PP of the wrestlers in the current study.
MP (W) = 9.3 (FFW) − 109.8 EQ.1
PP (W) = 14.1 (FFW) − 162.1 EQ.2
The results in the current study indicated that as percent of the mean values, the equation that predicted MP resulted in a substantially greater total error (TE; 19.9% of the mean) than the equation that predicted PP (8.3% of the mean). These findings indicated that the equation that was derived on nonathletes did not accurately estimate MP in the high school wrestlers. The equation for estimating PP, however, was valid when applied to the current sample of high school wrestlers. These findings supported previous studies that have shown that in adolescent males, exercise training improves the metabolic capabilities of the anaerobic glycolytic system, but not the phosphagen system.
Hans Luttikholt, Lars R. McNaughton, Adrian W. Midgley, and David J. Bentley
There is currently no model that predicts peak power output (PPO) thereby allowing comparison between different incremental exercise test (EXT) protocols. In this study we have used the critical power profile to develop a mathematical model for predicting PPO from the results of different EXTs.
The purpose of this study was to examine the level of agreement between actual PPO values and those predicted from the new model.
Eleven male athletes (age 25 ± 5 years, VO2max 62 ± 8 mL · kg–1 · min–1) completed 3 laboratory tests on a cycle ergometer. Each test comprised an EXT consisting of 1-minute workload increments of 30 W (EXT30/1) and 3-minute (EXT25/3) and 5-minute workload increments (EXT25/5) of 25 W. The PPO determined from each test was used to predict the PPO from the remaining 2 EXTs.
The differences between actual and predicted PPO values were statistically insignificant (P > .05). The random error components of the limits of agreement of ≤30 W also indicated acceptable levels of agreement between actual and predicted PPO values.
Further data collection is necessary to confirm whether the model is able to predict PPO over a wide range of EXT protocols in athletes of different aerobic and anaerobic capacities.
Rheanna Bulten, Sara King-Dowling, and John Cairney
, along with age and weight, was a significant predictor of peak power (PP), and boys exhibited higher PP values than girls. However, a limitation of this study was its focus on a typically developing (TD), nonclinical population. Many childhood chronic conditions affect physical activity participation
Nathan J. de Vos, Nalin A. Singh, Dale A. Ross, Theodora M. Stavrinos, Rhonda Orr, and Maria A. Fiatarone Singh
To determine the effect of training intensity on the contributions of force and velocity to improvements in peak power (PP) after explosive resistance training in older adults.
112 healthy older adults (69 ± 6 yr) were randomized to explosive resistance training at 20% (G20), 50% (G50), or 80% (G80) maximal strength (1-repetition maximum) for 8–12 wk (twice weekly, 5 exercises, 3 sets of 8 explosive concentric/slow eccentric repetitions) using pneumatic resistance machines or a nontraining control group (CON).
Force at peak power (FPP) increased significantly and similarly among training groups compared with CON. Velocity at peak power (VPP) did not improve significantly and remained similar between all groups. Force contributed significantly more to PP production in G80 and G50 than in CON. The change in PP was independently predicted by changes in fat-free mass in G80 and by changes in both FPP and VPP in G50 and G20.
Explosive resistance training in older adults results in the ability to produce higher PP outputs with heavier loads without loss of movement velocity. Moderate- to high-intensity training induced a greater relative contribution of force to PP production in this cohort.