This dissertation investigates the structural and dynamic aspects of football by employing Social Network Analysis (SNA) as the central methodological framework. While SNA has increasingly been used to analyze passing behavior on the pitch, its application remains limited in addressing deeper questions about team performance under different contextual conditions, gender-based tactical structures, and the global movement of players. This research addresses these gaps through three interrelated empirical studies, each targeting a specific and underexplored dimension of football.
The first study focuses on home and away differences in elite football by examining network-level indicators such as density and transitivity. It demonstrates that these metrics provide more nuanced insights into team cohesion and tactical flexibility than traditional performance statistics, thereby offering a novel approach to analyzing home advantage. The second study extends this line of inquiry by comparing passing networks in men’s and women’s top-tier football leagues. It finds that, despite well-documented physiological and stylistic differences, the structural organization of play—measured through network indicators—displays a high degree of similarity across gender, suggesting universality in tactical design and collaboration. The third study shifts focus from on-field dynamics to off-field phenomena, introducing the Squad-League Network (SLN) framework to explore global player mobility. By modeling relationships between national teams and domestic leagues across FIFA World Cups from 1950 to 2022, this study uncovers key trends such as the increasing concentration of talent in specific leagues, the emergence of regional pathways, and the reinforcing mechanisms of the “Matthew Effect.”
Together, these studies highlight the versatility of SNA in addressing both micro-level tactical behaviors and macro-level structural phenomena. The research contributes new tools for practitioners, while also enhancing theoretical understanding of football as a complex, evolving social system.
However, this research is not without limitations. The reliance on passing network data in the first two studies restricts the analysis to specific aspects of team performance, potentially overlooking other crucial factors such as individual player skills, physical conditioning, or tactical instructions beyond passing behavior. Additionally, the focus on elite-level competitions and players in all three studies may introduce selection bias, limiting the generalizability of findings to lower-tier leagues or amateur football. The third study’s emphasis on FIFA World Cup participants and associated leagues also carries inherent biases due to qualification processes and regional disparities in football development. These constraints suggest that while the presented findings offer valuable insights, they should be interpreted within the context of the available data and scope of the analyses.
Ultimately, this dissertation contributes to the broader discourse on sports, society, and human behavior. By leveraging the power of network analysis, this research not only deepens our understanding of football but also provides a foundation for addressing complex questions about talent distribution, competitive parity, and the globalization of sports. As the field of sports science continues to evolve, the insights from this research will serve as a valuable resource for academics, practitioners, and policymakers alike, fostering the development of more equitable and inclusive sports ecosystems.
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This dissertation investigates the structural and dynamic aspects of football by employing Social Network Analysis (SNA) as the central methodological framework. While SNA has increasingly been used to analyze passing behavior on the pitch, its application remains limited in addressing deeper questions about team performance under different contextual conditions, gender-based tactical structures, and the global movement of players. This research addresses these gaps through three interrelated em...
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