Prediction of Maximal Vertical Jumps during the Entire Season in NCAA Division 1 Women Basketball Players

Abstract

Purpose: The purpose of this study was to develop a prediction model of weekly maximum jump height (JHmax) performance as a measure of readiness from external workload measures during practice and games, measures of volume-load during resistance training, and self-reported sleep quality, stress, and recovery in NCAA Division 1, women basketball players during the entire season. Methods: Twelve female participants (age = 21.3 ± 1.6 yrs; ht = 171.6 ± 7.1 cm; wt = 67.9 ± 5.3 kg) who were cleared for full participation were recruited to participate in the study. Workload (WL) and work intensity (WI) were measured during every practice and game during the entire official season. The following independent variables were entered into a multivariate regression model to predict JH_max performance across each week in the season using a 7-day period prior to assessment: WL, WI, and Work Density (WD) (WL x WI), self-reported sleep quality (SL), stress (STR), and recovery (REC), total resistance training volume-load (RTV), prior week’s JH_max (Sign), week of the season (Week), and pre-season vs in-season (Season). JH_max was the dependent measure assessed prior to the season and every Monday. Results: The resultant model was statistically significant with an r² of 71 %. All variables were significant predictors of JH_max except SL and REC. Conclusions: A trend of lower WL and RTV and greater WI and STR had a positive effect on the following JH_max. Analyzing the 7-day period prior to JH_max assessment, high WD scores by manipulation of WL and WI six days prior had a positive influence on JH_max while lower scores were warranted the day before the test. High WL with low WI were indicated three days prior. Finally, controlling for the other variables, JH_max tended to decrease across the in-season indicating a need to reduce external loads in the following week when JH_max decreased to enhance recovery.