(49) ANALYSIS OF ATHLETE LOAD VIA WEARABLE MICROSENSORS ACROSS A WOMEN’S COLLEGIATE BASKETBALL SEASON

BACKGROUND: Wearable microsensor technology enables the quantification of practice and competition-based workloads of athletes. Limited research exists exploring such workloads in women’s collegiate basketball.

Purpose: To investigate athlete workload metrics during practices and games throughout a competitive basketball season.

Methods: National Collegiate Athletic Association Division I women’s basketball athletes (n=15; mean ± SD; age: 19.0 ± 1.3 years; weight: 73.8 ± 6.6 kg; height: 180.5 ± 6.7 cm) were equipped with wearable microsensors for practices (n=54) and games (n=28). Assessed metrics included: energy expenditure (kilocalories [kcals]), relative energy expenditure (kcal/min), training load (AU), maximal heart rate (HR_max, bpm), and average heart rate (HR_avg, bpm). High-minute players were classified as those who played ≥15 minutes per game (n=10); others were classified as low-minute players (n=5). Separate multivariate analysis of variance (MANOVA) assessed differences in loads between games and practices in high- and low-minute players (p< 0.05). Partial eta² effect sizes were determined and classified as: η²=0.01, small effect; η²=0.06, medium effect; and η²=0.14, large effect. RESULTS: Table 1 includes game and practice metrics. High-minute players had a higher energy expenditure (p< 0.001, η²=0.29), training load (p< 0.001, η²=0.14), and HR_max (p=0.01, η²=0.01) in games. Relative calorie expenditure (kcal/min, p< 0.001, η²=0.29) and HR_avg (p< 0.001, η²=0.08) were higher in practices. For low-minute players, all load metrics were higher in practices than games (energy expenditure: p=0.03, η²=0.01; relative energy expenditure: p< 0.001, η²=0.36; training load: p< 0.001, η²=0.16; HR_max: p=0.03, η²=0.01; HR_avg: p< 0.001, η²=0.45). When comparing loads between high and low-minute players during practice sessions, high-minute players had a higher energy expenditure (p< 0.001, η²=0.01), relative energy expenditure (p< 0.001, η²=0.01), and training load (p< 0.001, η²=0.01).

Conclusions: Findings indicate that high-minute players were exposed to higher absolute loads during games, likely due to a longer playing duration. Further, relative intensities (kcal/min) and HR_avg were higher in practice for high-minute players. Low-minute players experienced higher loads in practices compared to games. Lastly, high-minute players had higher energy expenditures and training loads in practices when compared to low-minute players. PRACTICAL APPLICATIONS: An individualized approach to periodization and load management is warranted to improve athlete health, performance, and reduce injury risk throughout a collegiate basketball season for high- and low-minute players. It is recommended that high-minute players receive adequate recovery, while low-minute players receive added exposure to game-level intensities to ensure they are maintaining appropriate fitness levels throughout the season for game scenarios.

Acknowledgements: The authors would like to thank the athletes for their participation in this study.