Exploring team dynamics through network analysis: A season review of an elite Portuguese soccer team
Abstract
Social network analysis was applied to investigate team dynamics and inter-player connections during matches to offer deeper insights into the organizational framework of an elite soccer team competing in the Portuguese First Division during the 2020–2021 season. This study aimed to assess the impact of match outcomes and the deployment of various tactical systems on the team’s macro network metrics, such as density and clustering coefficients. Data was collected from thirty-four matches, with each match’s passing interactions meticulously analyzed to construct adjacency matrices, thereby quantifying player interconnections. The study’s findings revealed a nuanced relationship between network metrics and match outcomes. Density was significantly higher in matches that ended in losses, suggesting a potential over-reliance on certain players or interactions in adverse scenarios. Conversely, matches won were characterized by higher clustering coefficients, indicating a more cohesive and interconnected team effort. The analysis of five different tactical systems revealed significant differences in density, pointing to the influence of tactical choices on player interactions. No significant differences were found in clustering coefficients across the tactical systems, suggesting a consistent internal team cohesion irrespective of the strategy employed. These insights highlight the utility of network analysis in enhancing the understanding of team dynamics and strategic planning. This study underscores the potential of such analytical approaches to inform better tactical decisions and optimize team performance, ultimately contributing to a more sophisticated level of competitive analysis in professional sports.
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