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Relationship Between Individual Workload, Training Impulse, and Game Performance in Women Collegiate Basketball
Faith S A Brown1,2, Jennifer B Fields1,3, Andrew R Jagim1,4
1Frank Pettrone Center for Sports Performance, George Mason University, Fairfax, Virginia.
Abstract:
Brown, FSA, Fields, JB, Jagim, AR, Miller, A, Baker, RE, and Jones, MT. Relationship between individual workload, training impulse, and game performance in women collegiate basketball athletes. J Strength Cond Res XX(X): 000-000, 2026-The purpose was to quantify game external load (EL) demands and explore relationships between EL, internal load (IL), and measures of basketball performance across a competitive season in women basketball athletes (n = 7). Data were collected by an inertial measurement unit microsensor and heart rate monitor for games (n = 28) and practices (n = 61). Playerload™ (PL), training impulse (TRIMP), and player efficiency (PE) were used to quantify EL, IL, and basketball performance, respectively. Descriptive statistics were used to quantify individual athlete PE, IL, and EL game measures, and game statistics for each game and stratified by position type. Repeated-measures correlations assessed relationships between PL, TRIMP, and PE. Two separate location scale models (PL, TRIMP) assessed the effect of session, position, PE, and previous day workload (PL lag, TRIMP lag). Results showed small to very large relationships (r = 0.21-0.85) between PL, TRIMP, and PE. Previous day workloads (PL, TRIMP) positively affected next-day load. Playerload increased as PE increased. Guards experienced higher within person variability of PL than forward or center positions. Athletes experienced high within person variability of PL (25.50 AU) and TRIMP (20.90 AU) across the season. The average TRIMP remained consistent across the season (230.2 AU) but varied between athletes (B = 0.90 [95% CI: 0.30-6.50]). Results suggest preceding day workload is associated with next-day workload and player performance, with higher EL being associated with higher PE. Furthermore, higher variability among athletes indicates other factors may affect workload across the season beyond sport training.
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