增强团队动态:通过社交网络分析揭示协同效应 在职业篮球中
Bufan Wei1, Zengyu Li1, Changjing Zhou1
1School of Athletic Performance, Shanghai University of Sports, Shanghai, China.
Acta psychologica
|October 18, 2025
概括
这项研究使用集群和社交网络分析重新定义了中国篮球协会 (CBA) 球员角色. 十个角色显著影响了团队的成功,核心球处理器提高了表现,而球主导得分者阻碍了这一点.
科学领域:
- 运动分析 运动分析
- 篮球表现分析 篮球表现分析
- 运动中的网络科学.
背景情况:
- 了解球员角色对于优化职业篮球团队表现至关重要.
- 以前的角色分类可能无法完全捕捉现代篮球阵容中的动态相互作用.
- 中国篮球协会 (CBA) 为分析球员角色提供了一个独特的背景,因为它具有特殊的竞争格局.
研究的目的:
- 在CBA中重新定义玩家角色,使用基于进攻和防守类型的数据驱动集群模型.
- 通过使用社交网络分析 (SNA) 来分析高性能阵容中的球员位置协同作用和网络效应.
- 确定与进攻,防守和整体净评分卓越相关的关键球员角色.
主要方法:
- 集群模型应用于5个赛季 (2018-2023) 的1813名CBA球员的进攻和防守类型数据.
- 社交网络分析 (SNA) 用于检查阵容协同作用和球员联系.
- 分析了来自20个CBA俱乐部的22,661个阵容样本.
主要成果:
- 通过聚类确定了19个不同的参与者角色.
- 其中只有10个角色与优秀的团队阵容有很高的相关性.
- C6核心球处理者角色对队友表现产生了积极的影响,而C3球主导得分者角色对其他人产生了负面影响.
- 球员角色的协同作用是显而易见的,特定的互动 (例如,C1球外射手与C6球处理器和C2多功能大) 是关键的.
结论:
- 玩家角色定义可以使用高级分析来改进,提供对个人贡献的更细致的理解.
- 特定的球员角色及其相互作用在CBA中显著决定了球队的成功.
- 这些发现为教练在团队组成和战略开发方面提供了可操作的见解.
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