Soccer Analytics Using Touch-by-Touch Match Data
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This paper discusses several soccer analytics directions exploiting detailed ball touch data from a soccer game. The topics discussed include visualizing team formations and quantifying territorial advantage; determining the network-based structural properties of team play, and computing the importance of individual players for the team interactions. The proposed ideas are illustrated using the data from a real-life Barclays Premier League game, which was made available by StatDNA.
KeywordsSpan Tree Social Network Analysis Gini Coefficient Centrality Score Soccer Game
We would like to thank Jaeson Rosenfeld, CEO of StatDNA for providing the data used in this study.
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