Amir Hossein Ahmadi - Master of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran
Babak Teimourpour - Assistant Professor of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran
Mahtab Mahbood - Master of Computer Engineering, Amirkabir University of Technology, Tehran, Iran

Statistics, extraction, analysis are vital in sports science. Information technology and data science will significantly increase the quality of research and decisions of sports clubs and organizations. Currently, many coaches and sports institutions use analytics and statistics that are calculated manually. Sports science shows that winning a match depends on different factors.The purpose of the research is to improve team performance by analyzing social networks, communication networks (such as players' passes and transactions during the match), and analyzing repetitive areas. These results are done by analyzing the data collected from ۴ matches of the Persepolis team, including three matches from the first half of the Iranian Premier League in ۲۰۱۸-۱۳۹۹ and a Persepolis match against Al-Sharjah. This research examines the issue from two interconnected aspects: ۱- Examining the performance of players individually and as part of a social network. ۲- explore the communication network between players and land areas. This analysis uses the innovative method of identifying and classifying motifs.

social network analysis, Graph Analysis, Motif, Frequent Subgraph, centrality