Sanders Gabriel J, Skodinski Stacie, Peacock Corey A
College of Education, Criminal Justice and Human Services, University of Cincinnati, Cincinnati, OH 45221, USA.
College of Healthcare Sciences, Nova Southeastern University, Fort Lauderdale, FL 33328, USA.
Sensors (Basel). 2024 Dec 30;25(1):151. doi: 10.3390/s25010151.
The purpose was to create a systematic approach for analyzing data to improve predictive models for fatigue and neuromuscular performance in volleyball, with potential applications in other sports. The study aimed to assess whether average, peak, or peak-to-average ratios of countermovement jump (CMJ) force plate metrics exhibit stronger correlations and determine which metric most effectively predicts performance. Data were obtained from nine division I female volleyball athletes over a season, recording daily jump loads (total jumps, jump counts >38.1 cm (Jumps 38+), and >50.8 cm (Jumps 50+) in height) and comparing these with CMJ force metrics recorded the next day, both average and peak. Correlations and regressions were utilized to assess the relationship and predictive value for jump loads on CMJ test data. The findings revealed that the most significant ( < 0.001 for all) negative correlations ( ranged from -0.384 to -0.529) occurred between Jumps 50+ and the average CMJ test variables. Furthermore, there were no significant relationships between jump loads and peak-to-average ratios ( ≥ 0.233). Average CMJ force metrics and Jumps 50+ provide slightly more predictive (up to 28% of variability) potential for fatigue modeling of neuromuscular performance.
目的是创建一种系统的数据分析方法，以改进排球运动中疲劳和神经肌肉表现的预测模型，并探讨其在其他运动项目中的潜在应用。该研究旨在评估反向纵跳（CMJ）测力台指标的平均值、峰值或峰均比是否呈现更强的相关性，并确定哪种指标能最有效地预测运动表现。研究数据来自9名一级联赛女子排球运动员一个赛季的记录，包括每日的跳跃负荷（总跳跃次数、高度大于38.1厘米的跳跃次数（38+厘米跳跃次数）以及大于50.8厘米的跳跃次数（50+厘米跳跃次数）），并将这些数据与次日记录的CMJ测力指标（平均值和峰值）进行比较。利用相关性和回归分析来评估跳跃负荷与CMJ测试数据之间的关系及预测价值。研究结果显示，50+厘米跳跃次数与CMJ测试变量平均值之间存在最显著的负相关（所有相关性均<0.001，范围为-0.384至-0.529）。此外，跳跃负荷与峰均比之间不存在显著关系（≥0.233）。CMJ测力指标平均值和50+厘米跳跃次数为神经肌肉表现的疲劳建模提供了稍强的预测潜力（高达28%的变异性）。
