Using Diagnostic Analysis to Discover Offensive Patterns in a Football Game
Football is a popular team sport, for which analyzing a team strategies can reveal useful information for understanding and improving a team’s performance. For this purpose, a promising approach is to analyze data collected about a match using data mining algorithms. However, designing such approach is not trivial as a football match involves both the time dimension and the spatial dimension. In this paper, a diagnostic analysis based approach is proposed, which consists of preparing data from a match by considering the spatial dimension and then extracting sequential rules from the data. The proposed approach is illustrated in a case study to analyze the match between Germany and Italy at the 2012 European Championship. Results of this study show that threatening offensive patterns from the Germany team are identified, illustrating complex interactions between players for performance analysis.
KeywordsFootball Performance analysis data mining Sequential rules European Championship
The authors would like to thank all the participants involved in this work. Markus Kraus and Simon Scholz are acknowledged for their important data collection and comments. The Project is sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry and also supported by “the Fundamental Research Funds for the Central Universities (Youth Scholars Program of Beijing Normal University)”.
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