Asia FOOTBALL Centrality Analysis Using Pass Information: Centered on the 2018 Russia World Cup
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Purpose: The core purpose of this study was to objectively evaluate the performance of Asian countries partic-ipating in the 2018 FIFA World Cup using social network analysis. Method: The subject of study included 5 Asian countries participated in the 2018 FIFA World Cup in Russia, using pass data for each position based on official data provided by FIFA. The processed data are made into symmetric matrices and the research perform a centrality analysis using Ucinet6, a social network program. Results: The results of the study are as follows. First, when the pass success rate was more than 80%, the ball possession rate was more than 50%, and the actual ball possession time was also confirmed to have 30 minutes. Second, the centrality analysis confirmed that players with high degree centrality also have a high closeness cen-trality, which can be information that can objectively evaluate major attack directions and key players. Conclusion: The results of this study can be used as an objective indicator to identify key players and evaluate their performance through passes by players in team sports events. However, due to the nature of the World Cup games, it is difficult to secure a lot of match data by country, and it is a pity that players who have not participat-ed in the games due to injury cannot be evaluated. Based on the results shown in this research, we hope that it will be used as a new evaluation method to identify key players and objectively analyze each country's game pat-terns in order to advance to the 2022 Qatar World Cup finals, and it can be used as an analysis method that can objectively evaluate not only soccer games but also other team sports games through social network analysis.
Abstract
Purpose: The core purpose of this study was to objectively evaluate the performance of Asian countries partic-ipating in the 2018 FIFA World Cup using social network analysis. Method: The subject of study included 5 Asian countries participated in the 2018 FIFA World Cup in Russia, using pass data for each position based on official data provided by FIFA. The processed data are made into symmetric matrices and the research perform a centrality analysis using Ucinet6, a social network program. Results: The results of the study are as follows. First, when the pass success rate was more than 80%, the ball possession rate was more than 50%, and the actual ball possession time was also confirmed to have 30 minutes. Second, the centrality analysis confirmed that players with high degree centrality also have a high closeness cen-trality, which can be information that can objectively evaluate major attack directions and key players. Conclusion: The results of this study can be used as an objective indicator to identify key players and evaluate their performance through passes by players in team sports events. However, due to the nature of the World Cup games, it is difficult to secure a lot of match data by country, and it is a pity that players who have not participat-ed in the games due to injury cannot be evaluated. Based on the results shown in this research, we hope that it will be used as a new evaluation method to identify key players and objectively analyze each country's game pat-terns in order to advance to the 2022 Qatar World Cup finals, and it can be used as an analysis method that can objectively evaluate not only soccer games but also other team sports games through social network analysis.
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