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Seiichiro Takei, Kuniaki Hirayama and Junichi Okada

strength and conditioning settings. 2 , 3 Many studies have shown the effectiveness of the use of optimal load to generate the highest power output. 4 , 5 The reported optimal load for HPC varies among studies, ranging from 65% to 80% of 1-repetition maximum (1RM). 6 – 10 This inconsistency may derive

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Seiichiro Takei, Kuniaki Hirayama and Junichi Okada

strength and conditioning settings. 2 , 3 Many studies have shown the effectiveness of the use of optimal load to generate the highest power output. 4 , 5 The reported optimal load for HPC varies among studies, ranging from 65% to 80% of 1-repetition maximum (1RM). 6 – 10 This inconsistency may derive

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Matt R. Cross, Matt Brughelli, Pierre Samozino, Scott R. Brown and Jean-Benoit Morin

Purpose:

To ascertain whether force-velocity-power relationships could be compiled from a battery of sled-resisted overground sprints and to clarify and compare the optimal loading conditions for maximizing power production for different athlete cohorts.

Methods:

Recreational mixed-sport athletes (n = 12) and sprinters (n = 15) performed multiple trials of maximal sprints unloaded and towing a selection of sled masses (20–120% body mass [BM]). Velocity data were collected by sports radar, and kinetics at peak velocity were quantified using friction coefficients and aerodynamic drag. Individual force–velocity and power–velocity relationships were generated using linear and quadratic relationships, respectively. Mechanical and optimal loading variables were subsequently calculated and test–retest reliability assessed.

Results:

Individual force–velocity and power–velocity relationships were accurately fitted with regression models (R 2 > .977, P < .001) and were reliable (ES = 0.05–0.50, ICC = .73–.97, CV = 1.0–5.4%). The normal loading that maximized peak power was 78% ± 6% and 82% ± 8% of BM, representing a resistance of 3.37 and 3.62 N/kg at 4.19 ± 0.19 and 4.90 ± 0.18 m/s (recreational athletes and sprinters, respectively). Optimal force and normal load did not clearly differentiate between cohorts, although sprinters developed greater maximal power (17.2–26.5%, ES = 0.97–2.13, P < .02) at much greater velocities (16.9%, ES = 3.73, P < .001).

Conclusions:

Mechanical relationships can be accurately profiled using common sled-training equipment. Notably, the optimal loading conditions determined in this study (69–96% of BM, dependent on friction conditions) represent much greater resistance than current guidelines (~7–20% of BM). This method has potential value in quantifying individualized training parameters for optimized development of horizontal power.

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Liam P. Kilduff, Huw Bevan, Nick Owen, Mike I.C. Kingsley, Paul Bunce, Mark Bennett and Dan Cunningham

Purpose:

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.

Methods:

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.

Results:

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.

Conclusions:

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.

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Irineu Loturco, Timothy Suchomel, Chris Bishop, Ronaldo Kobal, Lucas A. Pereira and Michael R. McGuigan

conditioning activity and functional task. The same positive effects were also observed in soccer players, who experienced meaningful increases in 5-, 10-, and 20-m sprint performance after executing BHT under either heavy (85% 1RM) or optimum loading conditions 7 (ie, using the load able to maximize power

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Prue Cormie, Jeffrey M. McBride and Grant O. McCaulley

The objective of this study was to investigate the validity of power measurement techniques utilizing various kinematic and kinetic devices during the jump squat (JS), squat (S) and power clean (PC). Ten Division I male athletes were assessed for power output across various intensities: 0, 12, 27, 42, 56, 71, and 85% of one repetition maximum strength (1RM) in the JS and S and 30, 40, 50, 60, 70, 80, and 90% of 1RM in the PC. During the execution of each lift, six different data collection systems were utilized; (1) one linear position transducer (1-LPT); (2) one linear position transducer with the system mass representing the force (1-LPT+MASS); (3) two linear position transducers (2-LPT); (4) the force plate (FP); (5) one linear position transducer and a force plate (1-LPT+FP); (6) two linear position transducers and a force place (2-LPT+FP). Kinetic and kinematic variables calculated using the six methodologies were compared. Vertical power, force, and velocity differed significantly between 2-LPT+FP and 1-LPT, 1-LPT+MASS, 2-LPT, and FP methodologies across various intensities throughout the JS, S, and PC. These differences affected the load–power relationship and resulted in the transfer of the optimal load to a number of different intensities. This examination clearly indicates that data collection and analysis procedures influence the power output calculated as well as the load–power relationship of dynamic lower body movements.

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Irineu Loturco, Timothy Suchomel, Chris Bishop, Ronaldo Kobal, Lucas A. Pereira and Michael McGuigan

researchers to better select appropriate training strategies for their athletes. Thus, the aims of the present study were to: (1) analyze the correlations between bar-power outputs (under optimum loading conditions) and 1RM values (assessed in half-squat [HS] and jump squat [JS] exercises), and multiple

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Prue Cormie, Jeffrey M. McBride and Grant O. McCaulley

The purpose of this investigation was to examine the impact of load on the power-, force- and velocity-time curves during the jump squat. The analysis of these curves for the entire movement at a sampling frequency of 200–500 Hz averaged across 18 untrained male subjects is the most novel aspect of this study. Jump squat performance was assessed in a randomized fashion across five different external loads: 0, 20, 40, 60, and 80 kg (equivalent to 0 ± 0, 18 ± 4, 37 ± 8, 55 ± 12, 74 ± 15% of 1RM, respectively). The 0-kg loading condition (i.e., body mass only) was the load that maximized peak power output, displaying a significantly (p ≤ .05) greater value than the 40, 60, and 80 kg loads. The shape of the force-, power-, and velocity-time curves changed significantly as the load applied to the jump squat increased. There was a significantly greater rate of power development in the 0 kg load in comparison with all other loads examined. As the first comprehensive illustration of how the entire power-, force-, and velocity-time curves change across various loading conditions, this study provides extensive evidence that a load equaling an individuals body mass (i.e., external load = 0 kg) maximizes power output in untrained individuals during the jump squat.

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Hamdi Jaafar, Majdi Rouis, Elvis Attiogbé, Henry Vandewalle and Tarak Driss

Purpose:

To verify the hypothesis that the peak power (PP) of a Wingate test (WT) is an underestimation of maximal power (Pmax) computed from the force–velocity test (FVT), to examine possible fatigue effect on Pmax, and to investigate the effect of load on mean power (MP) and fatigue index (FI) during a WT in trained and recreational men.

Methods:

Ten recreational (22.9 ± 1.7 y, 1.81 ± 0.06 m, 73.3 ± 10.4 kg) and 10 highly trained subjects (22.7 ± 1.4 y, 1.85 ± 0.05 m, 78.9 ± 6.6 kg) performed 2 WTs with 2 loads (8.7% and 11% of body mass [BM]) and an FVT on the same cycle ergometer, in randomized order.

Results:

Optimal load was equal to 10% BM in recreational participants. Given the quadratic relationship between load and power, the underestimation of Pmax was lower than 10% for the average values of trained and recreational participants with both loads. However, PP with a load equal to 8.7% BM was a large underestimation (~30%) of Pmax in the most powerful individuals. In addition, PP was not greater than Pmax of FVT for the same load. FI was independent of the load only if it was expressed relative to PP. The optimal load for MP during WT was close to the optimal load for PP.

Conclusions:

The optimal load for WT performance should be approximately equal to 10% BM in recreational subjects. In powerful subjects, the FVT appears to be more appropriate in assessing maximal power, and loads higher than 11% BM should be verified for the WT.

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Kym J. Williams, Dale W. Chapman, Elissa J. Phillips and Nick Ball

quasi-linear force–velocity relationship is reported, 4 with empirical evidence supporting a load equal to body mass as the optimal load to maximize system power during a countermovement jump (CMJ). 5 – 7 Long-term specialized training can have a profound influence on a muscle’s contractile profile, 8