Document Type : Research Paper
Authors
1 Ph.D. Student in Motor Behavior, Kharazmi University
2 Assistant Professor of Sport Bio Mechanic, Sport Sciences Research Institute
3 Professor of Motor Behavior, Kharazmi University
Abstract
The purpose of this study was to use a new method based on social networking techniques to identify self-organizing maps in football teams. The research approach was observational. Based on the data extracted from the FIFA site, after each game, network indicators were organized at two levels of micro and macro, and three official matches of the national football team of Iran were analyzed in the 2018 World Cup. Based on Available Data The network indicators were organized at two levels of micro and macro, and three official matches of the Iranian national team were analyzed in the 2018 World Cup. A total of 517 offensive phases were analyzed in three games. For each attacking phase, a series of proximity matrices was created, which analyzed the density, clustering and game center based on the relative position of the player in the field at two levels using the Nod XL software. The results provided explanations for the tactical performance and features of the Iranian national team networks in these games, and low levels of density and clustering coefficients indicated weak tactical solutions in the offensive phase. The result is a comprehensive explanation for the tactical team performance. Iran nationalized in these games. In general, the findings of this study provide operational strategies that can be used to examine the structure of the team network and its indicators in football teams, and to educate the instructors in understanding the characteristics of teamwork, improving decision making during the match, and providing a protocol Appropriate training exercises.
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