TY - JOUR ID - 164095 TI - Social Network Analysis of Football Communications by Finding Motifs JO - International Journal of Web Research JA - IJWR LA - en SN - 2645-4335 AU - Ahmadi, Amir Hossein AU - Teimourpour, Babak AU - Mahbood, Mahtab AD - Master of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran AD - Assistant Professor of Information Technology Engineering, Tarbiat Modares University, Tehran, Iran AD - Master of Computer Engineering, Amirkabir University of Technology, Tehran, Iran Y1 - 2022 PY - 2022 VL - 5 IS - 2 SP - 39 EP - 46 KW - social network analysis KW - Graph Analysis KW - Motif KW - Frequent Subgraph KW - centrality DO - 10.22133/ijwr.2022.321880.1110 N2 - 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 4 matches of the Persepolis team, including three matches from the first half of the Iranian Premier League in 2018-1399 and a Persepolis match against Al-Sharjah. This research examines the issue from two interconnected aspects: 1- Examining the performance of players individually and as part of a social network. 2- explore the communication network between players and land areas. This analysis uses the innovative method of identifying and classifying motifs. UR - https://ijwr.usc.ac.ir/article_164095.html L1 - https://ijwr.usc.ac.ir/article_164095_3255014a7a71f0855b8bdd3e1e9e165d.pdf ER -