基于加速度计的训练负荷分析法评估排球运动成绩

Gabriel J. Sanders, Brian Boos, Frank Shipley, Cory M. Scheadler, Corey A. Peacock
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引用次数: 8

摘要

前言:目的是量化排球运动员基于加速度计的工作量,并利用神经肌肉疲劳跳跃测试来评估整个比赛赛季的场上表现。方法:首先,对一级排球运动员在每次训练和比赛中使用经过验证的可穿戴微传感器设备(Catapult Sports)进行监测。为了评估神经肌肉疲劳,每周进行一次进路跳跃(AJ)测试。每场比赛都记录了场上的数据。结果:利用正向线性回归模型,低强度减速、中强度和高强度加速、低强度和高强度跳跃占AJ检验评估的每周相对功率变化的91.7% (p < 0.001)。在这些变量中,只有高强度的跳跃在赢球(49.6±26.7)和输球(69.2±39.8)之前的练习之间有显著差异(p = 0.035)。此外,命中率显著提高。266±0.190胜;0.130±0.129损耗;P = 0.05)。结论:在整个比赛赛季中,入路跳跃表现的变化是多方面的;然而,在练习中限制高强度的跳跃可能有利于优化排球的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Accelerometer-Based Training Load Analysis to Assess Volleyball Performance
Introduction: The purpose was to quantify a volleyball athlete’ s accelerometer-based workloads and utilize a neuromuscular fatigue jump test to assess on-court performance throughout a competitive season. Methods: One, Division I volleyball athlete was monitored throughout each practice and competitive game using a validated wearable microsensor device (Catapult Sports). To assess neuromuscular fatigue, an approach jump (AJ) test was completed weekly. On-court statistics were recorded each game. Results: Utilizing a forward linear regression model, low intensity decelerations, moderate and high intensity accelerations, and low and high intensity jumps accounted for 91.7% of the variation in weekly relative power assessed via AJ test (p < 0.001). Of those variables, only high intensity jumps were significantly (p = 0.035) different between practices that occurred prior to winning (49.6 ± 26.7) and losing (69.2 ± 39.8) game performances. Additionally, hitting percent was significantly better (.266 ± .190 win; .130 ± .129 loss; p = 0.05) in winning performances. Conclusions: Alterations in approach jump performance throughout a competitive season is multifaceted; however, limiting high intensity jumps in practice may be advantageous to optimize volleyball performance.
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