Understanding team performance in professional football increasingly benefits from network science, which models players as nodes and their interactions as functional links. While Social Network Analysis (SNA) provides valuable structural insights, it often fails to capture the probabilistic nature of possession. This exploratory study introduces an integrated methodological framework that combines static SNA with a Markov-spectral model of ball circulation to analyse the Portuguese National Team across two high-stakes 2025 Nations League finals matches. This approach moves beyond describing who is connected to quantifying how possession flows through the team network. Match event data were obtained via the Wyscout ® platform, with all passing actions by Portugal extracted. The framework combined SNA (using uPATO ® ) with Markov-spectral analysis (implemented in MATLAB ® ) to compute indices of passing uncertainty, diffusion speed, navigability, and network robustness. The results suggested that (i) SNA identified key players as crucial hubs for ball circulation at the micro level, while indicating a cohesive team structure with adaptable macro-level properties; and (ii) Markov-spectral quantification showed descriptive between-match variations, with the second match displaying higher Entropy (2.84 vs 2.77 bits/pass), suggestive of greater unpredictability, and a larger Spectral Gap (0.53 vs 0.45), indicative of faster potential diffusion of possession. Overall, this integrated approach demonstrates the feasibility of profiling team coordination through both structural configuration and stochastic flow properties. The Markov-spectral framework complements traditional SNA by providing quantifiable indices related to passing variability, network navigability, and structural cohesion, offering a multi-layered, proof-of-concept toolkit for analysing collective performance.
Gama et al. (2026) studied this question.