Social Network Analysis of Football Communications by Finding Motifs
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University of science and culture
2022-07-01
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| Series: | International Journal of Web Research |
| Subjects: | |
| Online Access: | https://ijwr.usc.ac.ir/article_164095_3255014a7a71f0855b8bdd3e1e9e165d.pdf |
| _version_ | 1826901622377152512 |
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| author | Amir Hossein Ahmadi Babak Teimourpour Mahtab Mahbood |
| author_facet | Amir Hossein Ahmadi Babak Teimourpour Mahtab Mahbood |
| author_sort | Amir Hossein Ahmadi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2025-02-17T07:27:07Z |
| format | Article |
| id | doaj.art-2fbde69ae9e5492bac0f500dba7a8b7e |
| institution | Directory Open Access Journal |
| issn | 2645-4343 |
| language | English |
| last_indexed | 2025-02-17T07:27:07Z |
| publishDate | 2022-07-01 |
| publisher | University of science and culture |
| record_format | Article |
| series | International Journal of Web Research |
| spelling | doaj.art-2fbde69ae9e5492bac0f500dba7a8b7e2025-01-04T09:45:08ZengUniversity of science and cultureInternational Journal of Web Research2645-43432022-07-0152394610.22133/ijwr.2022.321880.1110Social Network Analysis of Football Communications by Finding MotifsAmir Hossein Ahmadi0Babak Teimourpour1Mahtab Mahbood2Master of Information Technology Engineering, Tarbiat Modares University, Tehran, IranAssistant Professor of Information Technology Engineering, Tarbiat Modares University, Tehran, IranMaster of Computer Engineering, Amirkabir University of Technology, Tehran, IranStatistics, 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.https://ijwr.usc.ac.ir/article_164095_3255014a7a71f0855b8bdd3e1e9e165d.pdfsocial network analysisgraph analysismotiffrequent subgraphcentrality |
| spellingShingle | Amir Hossein Ahmadi Babak Teimourpour Mahtab Mahbood Social Network Analysis of Football Communications by Finding Motifs International Journal of Web Research social network analysis graph analysis motif frequent subgraph centrality |
| title | Social Network Analysis of Football Communications by Finding Motifs |
| title_full | Social Network Analysis of Football Communications by Finding Motifs |
| title_fullStr | Social Network Analysis of Football Communications by Finding Motifs |
| title_full_unstemmed | Social Network Analysis of Football Communications by Finding Motifs |
| title_short | Social Network Analysis of Football Communications by Finding Motifs |
| title_sort | social network analysis of football communications by finding motifs |
| topic | social network analysis graph analysis motif frequent subgraph centrality |
| url | https://ijwr.usc.ac.ir/article_164095_3255014a7a71f0855b8bdd3e1e9e165d.pdf |
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