(10) MONITORING EXTERNAL TRAINING LOADS AND COUNTERMOVEMENT JUMP VARIABLES IN DIVISION 1 WOMEN’S COLLEGIATE BASKETBALL PLAYERS OVER THE PREPARATORY PERIOD

With the accessibility of external monitoring technologies available within collegiate athletics, optimization of methods to quantify workloads accurately and efficiently has been prioritized.

Purpose: The purpose of this study was to investigate the efficacy of a commercially available external training load metric over the preparatory period in NCAA Division 1 female basketball players.

Methods: 11 female division 1 basketball athletes completed this study. Throughout six weeks of the preparatory period, external training load, total PlayerLoad^TM, was monitored for each participant during all mandatory basketball tactical and technical training sessions while countermovement jumps were performed weekly. To ensure reliability of external training load metrics, participants wore the same assigned sensor that sampled at a rate of 100 Hz in the same position between scapulae during all training sessions. All data were analyzed via the Catapult Sport software (Openfield, Catapult, Innovations, Melbourne, VIC, Australia) to quantify all participant movement. CMJ was routinely performed on the same day of the week and at the approximately same time of day each week. All data from CMJs were analyzed to quantify jump height (JH) and modified reactive strength index (mRSI) via Sparta Science technology which utilizes a commercially available force-plate system and proprietary software. Cumulative effect of physical activity (CTPL) was estimated as a sum of total PlayerLoad^TM up to each jump testing session divided by the number of days. Linear mixed-effects model was used to model data related to the efficacy of total PlayerLoad^TM and CTPL. Athletes (id) and their positions were examined as potential random effects.

Results: The best fit model suggested a high-order polynomial pattern between total PlayerLoad^TM and the number of days since the first jump testing session (figure 1) with a random effect of is only for the intercept and no random effect of position (marginal R² = 0.282; conditional R² = 0.446). Of particular note was that the fixed effect for the slope of the first order term was found to be positive. The intercept was estimated to be 512 (95% CI [466, 561]) while the slope was estimated to be 700 (95% CI [354, 1067]), respectively. Two different models suggested that CTPL has an inverse linear relationship with jump height (intercept estimated to be 14.64 (95% CI [-0.00504, -0.00106], marginal R² = 0.137) and mRSI (intercept estimated to be .442 (95% CI [-0.000221, -4.597081], marginal R² = 0.016; random effect of id for the intercept).

Conclusion: There can be a general increasing trend in workloads over the course of a preparatory period during a basketball season. CMJ height and mRSI may be used as indicators of the cumulative effect of workloads. PRACTICAL APPLICATION: Cumulative effect of physical activity may be tracked using CTPL derived from PlayerLoad^TM. Practitioners may be encouraged to monitor countermovement jump height or mRSI to understand performance response to the cumulative effect of physical activity.

Acknowledgements: None