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Predicting Lower Body Power from Vertical Jump Prediction Equations for Loaded Jump Squats at Different Intensities in Men and Women

Wright, Glenn A1; Pustina, Andrew A1; Mikat, Richard P1; Kernozek, Thomas W2

Journal of Strength & Conditioning Research: March 2012 - Volume 26 - Issue 3 - pp 648-655
doi: 10.1519/JSC.0b013e3182443125

Wright, GA, Pustina, AA, Mikat, RP, and Kernozek, TW. Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women. J Strength Cond Res 26(3): 648–655, 2012—The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PPest) for each load and for each prediction equation were compared with criterion PP values from a force plate (PPFP). The PPest values had high test-retest reliability and were strongly correlated to PPFP in both men and women at all relative loads. However, only the Harman equation accurately predicted PPFP at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

1Exercise and Sport Science Department; and 2Department of Health Professions, Human Performance Laboratory, University of Wisconsin La Crosse, La Crosse, Wisconsin

Address correspondence to Glenn A. Wright,

© 2012 National Strength and Conditioning Association