基于差异方程的网球比赛的多维动量链模型
Jingya Wang1, Sihang Guo2, Yuanyun Zhou2
1School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, Shenzhen, Guangdong, China.
PloS one
|December 31, 2024
概括
这项研究用一种新的多维模型量化了体育运动的势头. 更高的势头显著提高了球员的表现,增加了赢得网球比赛的可能性,预测准确率为80%.
科学领域:
- 运动科学 运动科学 运动科学
- 心理学 心理学 心理学
- 数据科学数据科学数据科学
背景情况:
- 势头被认为是影响竞争体育结果的关键因素.
- 了解势头对心理和行为的影响对于提高绩效至关重要.
研究的目的:
- 开发一个多维模型来量化网球运动员的运动动量动态.
- 调查运动势头,球员表现和比赛结果之间的关系.
主要方法:
- 利用统计分析和线性权重与差异方程来构建动量链模型.
- 整合了一个忘记曲线来改进动量波动分析.
- 分析了来自温布尔登2023男子单打比赛的7,284个得分点和6,870个额外的网球比赛.
主要成果:
- 占主导地位的玩家表现出更短的距离和更高的净冲击成功率,这表明从积极事件中获得性能提升.
- 较高的球员势头与得分概率的增加以及服务球队84%的胜利机会相关.
- 该模型在众多网球比赛中实现了超过80%的预测准确度.
结论:
- 势头显著影响运动员的心理和行为表现.
- 开发的模型提供了一种定量方法来理解和预测动量动态.
- 提出了利用"热手"现象的策略,并提出了基于动力机制的培训建议.
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