根据比赛前的预期和足球中的目标差异构建个人球员表现档案
Arian Skoki1, Boris Gašparović1, Stefan Ivić2
1Department of Computer Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia.
Sensors (Basel, Switzerland)
|March 13, 2024
概括
足球运动员足球运动员
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:
- 足球运动员的表现受到不可预测的游戏因素的影响,例如得分变化和预期.
- 对这些动态因素的反应来评估球员的努力对于绩效分析至关重要.
研究的目的:
- 开发一个数学模型,根据比赛前的预期和进球差 (GD) 来量化球员的努力.
- 加强目前评估球员对足球上下文因素的反应的方法.
主要方法:
- 使用GPS可穿戴传感器,以在5分钟间隔内跟踪玩家的能量消耗.
- 开发了一个数学模型,结合了游戏前的预期,耐力和GD动态.
- 在模型构建中使用粒子群和Nelder-Mead优化.
主要成果:
- 与基线方法相比,开发的模型显示出更高的性能.
- 实现了 396.87±61.42 的平均绝对误差 (MAE) 和 520.69±88.66.6 的根平均平方误差 (RMSE).
- 性能优于基线模型,MAE和RMSE值较低.
结论:
- 拟议的模型提供了一种改进的方法来评估玩家的努力,以应对上下文因素,特别是GD.
- 整合可穿戴数据和上下文因素可以提高对个人玩家特征和决策的理解.
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