李博,王雷.社会网络分析法研究足球比赛传球表现的可行性分析[J].北京体育大学学报,2017,40(8):112-119.
社会网络分析法研究足球比赛传球表现的可行性分析
Feasibility Analysis of Passing Performance in Football Match by Social Network Analysis
投稿时间:2016-12-02  
DOI:10.19582/j.cnki.11-3785/g8.2017.08.018
中文关键词:  关键词:足球比赛表现研究  社会网络分析  传球  2016欧洲杯
英文关键词:Keywords: performance analysis of football match  social network analysis  passing  2016 UEFA European Championship
基金项目:基金项目:江西省体育局体育科研课题一般项目(2015038)。通信作者:王雷。
作者单位
李博 东华理工大学体育学院江西 南昌 330013 
王雷 贵阳学院体育学院贵州 贵阳 550005 
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中文摘要:
      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年欧洲杯八分之一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,两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、右三个区域,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。
英文摘要:
      Abstract: This paper analyzed the passing performance in the match between Hungary and Belgium in 2016 UEFA European Championship by social network analysis in whole network, local area network and individual network levels, in order to detect the feasibility of passing performance in football match by social network analysis. Results: 1) In whole network level, the passing track network (PTN) of both teams had high density and short distance, most players had direct passing, and Belgium's forward passing was more obvious. 2) In local area network level, the cliques analysis showed that Hungary's passing was simple and mainly concentrated in the left wing , while Belgian’s was more flexible and was in the left, middle, and the right areas. The core/periphery analysis showed that most core players of Hungary team were middlefield players while Belgium’s were full back. The structure of core/periphery of Belgium was more reasonable. 3) In individual network level, the passing line of Hungary mainly relied on back field players, and the threaten passes were too less. Belgium’s passing line mainly relied on middle field players, it had more threaten passes than Hungary, and had smoother passing line than Hungary. 4) The result of this research showed that social network analysis is a proper technique to analyze performance in football match; network graph can show the passing trend directly, network density and distance means passing frequency and fluency, clique analysis can be used to analyze local passing, core/periphery analysis can be used to find out the core and marginalized groups in passing network, and the centrality analysis can evaluate the role of players in passing network.
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