通过gambis预测模型和网络相关性分析来探索体育记录演变的动态
Lu Tang1,2, Mingliang Yang1,2
1Department of Physical Education, Civil Aviation Flight University of China, Guanghan, China.
PloS one
|September 19, 2024
概括
分析1992-2018年间的体育记录,可以发现明显的进化模式. 运动中的表现演变与技术和能源支出有关,这表明加强体育训练可以改善运动记录.
科学领域:
- 运动科学 运动科学 运动科学
- 人体生理学 人体生理学
- 数据分析 数据分析
背景情况:
- 体育记录提供了对人类生理能力的见解.
- 目前的数据缺乏整合和分析跨体育运动的进化模式.
研究的目的:
- 分析体育纪录的进化模式.
- 研究记录进化,技术和生理因素之间的关系.
主要方法:
- 对24个男子田径,田径和游泳记录 (1992-2018) 的分析.
- 使用Gembris预测模型进行性能随机性.
- 皮尔森相关性分析,以评估事件之间的网络相关性.
主要成果:
- 游泳比赛的年度世界纪录变化比田径比赛更大.
- 冲刺,马拉松和游泳记录始终超过预测.
- 游泳,短跑和马拉松赛事之间存在显著的相关性.
结论:
- 体育纪录的演变受到技术和能源支出的影响.
- 建议加强基本体育训练,以提高体育表现.
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