数据处理方法对GNSS设备加速总结指标的影响在澳大利亚足球精英赛中
Susanne Ellens1, David L Carey1, Paul B Gastin1
1Sport, Performance, and Nutrition Research Group, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne 3000, Australia.
Sensors (Basel, Switzerland)
|July 13, 2024
概括
不同的数据处理方法显著改变了澳大利亚足球精英赛中的加速指标. 原始数据产生更高的值,而制造商处理大大减少了报告的努力和距离,影响了培训计划的设计.
科学领域:
- 运动科学 运动科学 运动科学
- 生物力学 生物力学
- 绩效分析 绩效分析
背景情况:
- 全球导航卫星系统 (GNSS) 追踪对于量化精英体育运动员负载至关重要.
- 来自GNSS数据的总结加速指标通常用于评估培训和匹配需求.
- 不同的数据处理协议对这些关键指标的影响仍然不完全理解.
研究的目的:
- 在精英澳大利亚足球中,使用三个不同的数据处理协议 (原始,定制,制造商) 来量化总结加速指标的差异.
- 评估这些处理方法对关键指标的影响,例如加速力度和在高强度区域内完成的距离.
主要方法:
- 利用了38名澳大利亚足球运动员在14场比赛中的10赫兹GNSS跟踪数据.
- 计算了两个常见的总结加速指标:力度数和中/高强度区域内的距离.
- 采用线性混合模型来分析原始,定制处理和制造商处理的数据的影响.
主要成果:
- 在这三种加工方法中观察到大量的差异.
- 与原始数据相比,制造商处理的数据报告的距离 (高达184倍) 和努力 (高达89倍) 显著降低.
- 与原始数据相比,定制处理的数据也显示了减少 (距离高达3.3倍,努力高达4.3倍).
结论:
- 数据处理协议极大地影响了总结加速指标的输出.
- 这些变化可能导致对体育需求 (体积,强度,频率) 的误解.
- 教练和研究人员必须了解处理方法的影响,以便准确的数据解释和有效的培训计划设计.
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