Social Network Analysis of Passes and Communication Graph in Football by mining Frequent Subgraphs

Sport is regarded as an inseparable part of human life. Currently, a growing trend is observed in people's interest in football teams. In general, a successful procedure in players' communication is one of the main factors required for the victory of that team. The present study aimed to perform analyzes based on the perspective of social and communication networks (such as player passes and in-game transactions) to improve team performance. The analysis was performed on data collected from three matches of the Persepolis club in the first half-season of the Iranian Premier League 2019–20. This research seeks to review this issue from two integral perspectives as follows: 1) evaluating the performance of individuals as a part of a social network, 2) investigating the communication network between players. To this aim, we used the innovative method of recognizing and classifying frequent subgroups in this analysis. It is worth noting that 20 persen of these routes were in the defensive line while 31 persen were in the defensive midfielder. However, there were no routes in the attacker line or offensive midfielder, which indicated a form of weakness. On the other hand, various types of node degrees, points, and n-pass cycles were calculated in other sections. The results revealed the weak performance of the connection bridge between the team's playmakers and the end-players for shooting the ball. Although these topics were discussed at a minor level and only three matches of a team, the results can be generalized to other issues.