在训练比赛和足球官方比赛中探索代谢功率和相当距离之间的相互作用:一种机器学习方法
Vincenzo Manzi1, Cristian Savoia2,3, Elvira Padua4
1Department of Humanities Science, Pegaso Open University, Naples, Italy.
Frontiers in physiology
|November 9, 2023
概括
这项研究表明,使用机器学习,代谢能力和相当距离可以区分训练比赛和官方足球比赛. 这些指标还验证了外部训练负载,有助于优化性能和减少受伤.
科学领域:
- 运动科学 运动科学 运动科学
- 生物机械分析 生物机械分析
- 业绩分析 业绩分析 业绩分析
背景情况:
- 区分训练比赛 (TG) 与官方足球比赛对于准确的负载管理至关重要.
- 了解代谢功率 (MP) 和相当距离 (ED) 之间的相互作用是评估训练负载的关键.
- 对于精英运动员来说,外部训练负载 (ETL) 和内部训练负载 (ITL) 需要有效的评估方法.
研究的目的:
- 探索足球训练比赛 (TG) 和官方比赛中代谢功率 (MP) 和等效距离 (ED) 之间的关系.
- 调查ETL (源自MP和ED) 和ITL (基于HR) 之间的关联,以确定标准的有效性.
- 应用机器学习技术来区分TG和基于MP和ED的官方匹配.
主要方法:
- 在11个月内利用了21名精英职业男性足球运动员的数据.
- 通过使用机器学习分类器 (KNN,决策树,随机森林,SVM) 分析了4269场训练比赛和380场官方比赛.
- 将爱德华兹的训练负载 (TL) 与MP衍生的TL相关联,以评估标准的有效性.
主要成果:
- 机器学习模型准确地区分了TG和官方匹配,AUC值从0.90到0.96,准确度从0.89到0.98.
- 在爱德华兹的TL和MP衍生的TL之间发现了显著的相关性 (r=0.590.87,p<0.001),证实了ETL的有效性.
- 尽管总体强度可能相似,MP和ED有效地区分了活动类型.
结论:
- 代谢功率和相当距离对于分析足球训练和比赛负载至关重要.
- 与官方比赛相比,TG与官方比赛的强度的不同基本因素需要进一步调查.
- 这些发现支持在精英足球中开发优化训练策略和伤害预防协议.
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