板球运动中的复杂网络分析：社团结构、球员角色与绩效指标
Complex Network Analysis in Cricket : Community structure, player's role and performance index
摘要：
运用网络分析方法研究运动队成员之间的互动，并以国际板球比赛中击球手之间的互动为例进行分析。我们为不同的球队生成了击球伙伴关系网络（BPN），并确定了网络的聚类系数、平均度、平均最短路径长度的精确值，并与Erd \text{ö} s-R \text{é} nyi模型进行了比较。我们观察到，网络表现出小世界行为，本质上是离散的。我们发现，最有联系的击球手不一定是最中心的，最中心的球员不一定是一个高击球率。我们研究的BPN的社区结构，并确定每个球员的角色的基础上，社区间和社区内的联系。我们观察到，{ \it DG Bradman爵士}，被认为是板球历史上最好的击球手，并没有占据网络$-$的中心位置，所谓的连接器枢纽。我们扩展我们的分析，量化的性能，相对重要性和影响，从团队中删除一个球员，根据不同的中心性分数。
英文摘要：
This paper describes the applications of network methods for understanding interaction within members of sport teams.We analyze the interaction of batsmen in International Cricket matches. We generate batting partnership network (BPN) for different teams and determine the exact values of clustering coefficient, average degree, average shortest path length of the networks and compare them with the Erd\text{ö}s-R\text{é}nyi model. We observe that the networks display small-world behavior and are disassortative in nature. We find that most connected batsman is not necessarily the most central and most central players are not necessarily the one with high batting averages. We study the community structure of the BPNs and identify each player's role based on inter-community and intra-community links. We observe that {\it Sir DG Bradman}, regarded as the best batsman in Cricket history does not occupy the central position in the network $-$ the so-called connector hub. We extend our analysis to quantify the performance, relative importance and effect of removing a player from the team, based on different centrality scores.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
