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使用基于数据挖掘的决策树分析来确定泰拳道胜败的决定因素:专注于基于证据的教练游戏分析
1Department of International Sport, Dankook University, Chungcheongnam-do, Korea.
BMC sports science, medicine & rehabilitation
|May 21, 2024
概括
对2022年世界羽毛球锦标赛的决策树分析揭示了获胜的关键因素. 胜利的情况,平局的情况和的数量显著决定了泰拳道比赛的结果.
科学领域:
- 运动科学 运动科学 运动科学
- 数据挖掘 数据挖掘
- 运动学 运动学
背景情况:
- 泰拳道 (TKD) 竞争分析对于提高表现至关重要.
- 了解获胜和失败的决定因素对于战略发展至关重要.
- 这项研究重点关注的是2022年世界羽毛球锦标赛女子比赛.
研究的目的:
- 确定泰拳道中胜败的关键决定因素.
- 将决策树分析,一种数据挖掘技术,应用于竞争数据.
- 分析影响泰拳道现行规则结果的因素.
主要方法:
- 利用了2022年世界锦标赛的272场女子泰拳道比赛的数据.
- 进行了独立的样本t测试,以比较赢球和输球组之间的游戏变量.
- 采用决策树分析来确定匹配结果的重要预测因素.
主要成果:
- 大多数游戏内容变量在赢球和输球组之间显示了统计学上显著的差异 (p < 0.05).
- 身体攻击的尝试和的数量没有显著差异 (p > 0.05).
- 决策树分析确定了胜利情况,平局情况和次数作为关键决定因素.
结论:
- 该研究提供了基于数据的洞察力,了解根据当前规则的泰拳道比赛动态.
- 识别出来的因素可以为提高绩效的辅导策略提供信息.
- 强调了数据挖掘技术在体育分析中的实用性.
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