社会网络分析法研究足球比赛传球表现的可行性分析
发布时间：2018-11-03 12:33
【摘要】：采用社会网络分析法从整体网、局域网、个体网层面,对2016年欧洲杯1/8决赛匈牙利对阵比利时比赛双方的传球表现进行分析,探析社会网络分析法用于足球比赛传球表现研究的可行性。研究结果表明:1)从整体网层面来看,2只球队的传球网络都具有密度高、距离短的特点,大部分球员之间都有过直接的传球联系,比利时队向前传球的趋势更加明显。2)从局域网层面来看,派系分析的结果显示了匈牙利的传球配合主要是集中在左路,打法单一,比利时队传球配合分散在左、中、右3个区域,打法更加灵活多变。核心边缘分析的结果显示,匈牙利传球网络核心球员大部分是后卫,比利时传球网络的核心球员大部分是中场,比利时队传球网络的核心边缘结构更合理。3)从个体网层面来看,匈牙利队传球过于依赖中后场球员,参与进攻的球员多但是有威胁的传球少,比利时队的传球主要围绕中场球员展开,参与进攻的球员少但有威胁的传球却更多,传球也比匈牙利更加顺畅。4)社会网络分析法用于足球比赛传球表现研究是可行的,传球网络图可以直观的窥探传球趋势,网络的密度和距离可以表示传球的频度和流畅度,派系分析可以研究局部传球情况,核心-边缘分析可以找出传球网络中的核心群体和边缘群体,中心性分析可以评估球员在传球网络中扮演的角色。
[Abstract]:Using the social network analysis method, from the whole network, the local area network, the individual net level, carries on the analysis to the 2016 European Cup 1 / 8 final Hungary against Belgium's both sides passing performance, To explore the feasibility of using social network analysis method to study the performance of passing in football matches. The results show that: 1) from the overall network level, the passing networks of the two teams have the characteristics of high density and short distance, and most of the players have direct passing connections. From the local area network level, the results of faction analysis show that Hungary's passing cooperation is mainly concentrated on the left side, playing a single way, and the Billy team's passing cooperation is scattered in the left, in the middle. Right 3 regions, play more flexible. The core edge analysis shows that most of the core players in the Hungarian pass network are defenders, and the core players in the Belgian passing network are mostly midfield players. The core edge of Billy's passing network is more reasonable. 3) from the individual point of view, Hungary's passing is too dependent on the middle and back court players, with more attacking players but less threatening passes. Pyrenees' passing revolves around midfield players, with fewer but more threatening passes and smoother passes than Hungary. 4) Social network analysis is feasible for ball performance research in football. Passing network graph can intuitively pry the passing trend, the density and distance of the network can indicate the frequency and fluency of passing, and faction analysis can study the situation of local passing. The core-edge analysis can find out the core group and the edge group in the passing network, and the central analysis can evaluate the player's role in the passing network.
【作者单位】： 东华理工大学体育学院;贵阳学院体育学院;
【基金】：江西省体育局体育科研课题一般项目(课题编号:2015038)
【分类号】：G843
本文编号：2307801
[Abstract]:Using the social network analysis method, from the whole network, the local area network, the individual net level, carries on the analysis to the 2016 European Cup 1 / 8 final Hungary against Belgium's both sides passing performance, To explore the feasibility of using social network analysis method to study the performance of passing in football matches. The results show that: 1) from the overall network level, the passing networks of the two teams have the characteristics of high density and short distance, and most of the players have direct passing connections. From the local area network level, the results of faction analysis show that Hungary's passing cooperation is mainly concentrated on the left side, playing a single way, and the Billy team's passing cooperation is scattered in the left, in the middle. Right 3 regions, play more flexible. The core edge analysis shows that most of the core players in the Hungarian pass network are defenders, and the core players in the Belgian passing network are mostly midfield players. The core edge of Billy's passing network is more reasonable. 3) from the individual point of view, Hungary's passing is too dependent on the middle and back court players, with more attacking players but less threatening passes. Pyrenees' passing revolves around midfield players, with fewer but more threatening passes and smoother passes than Hungary. 4) Social network analysis is feasible for ball performance research in football. Passing network graph can intuitively pry the passing trend, the density and distance of the network can indicate the frequency and fluency of passing, and faction analysis can study the situation of local passing. The core-edge analysis can find out the core group and the edge group in the passing network, and the central analysis can evaluate the player's role in the passing network.
【作者单位】： 东华理工大学体育学院;贵阳学院体育学院;
【基金】：江西省体育局体育科研课题一般项目(课题编号:2015038)
【分类号】：G843
【相似文献】
相关期刊论文 前1条
1 郭立亚,朱瑜;社会网络分析法在运动队结构和人际特征分析中的应用探究[J];中国体育科技;2005年05期
，本文编号：2307801
本文链接：https://www.wllwen.com/jiaoyulunwen/tylw/2307801.html
