Alves, RicardoDias, Gonçalo Nuno FigueiredoNunes, Nuno AndréMartins, Fernando Manuel LourençoQuerido, Sérgio M.Vaz, Vasco2026-05-182026-05-182025-10Alves, R.; Dias, G.; Nunes, N.A.; Martins, F.; Querido, S.M.; Vaz, V. Positional Influence in Football Passing Networks: An Analysis of the Tactical Systems and Match Outcomes. Appl. Sci. 2025, 15, 11513. https://doi.org/10.3390/ app1521115132076-3417http://hdl.handle.net/10400.26/63175This study analysed how tactical systems and match outcomes influence micro-level passing network metrics across playing positions in a professional football team competing in the Portuguese First Division during the 2020–2021 season. It examined how structural variation affects Degree Centrality, Degree Prestige, and Proximity Prestige across tactical systems (1-4-1-4-1, 1-4-3-3, 1-3-4-3) and outcomes (win, loss, draw) in different positions. Data from 28 league matches were used, with adjacency matrices constructed from teammate interactions. Players were grouped into six positions: goalkeepers, fullbacks, central defenders, central midfielders, wingers, and strikers. One-way ANOVA revealed significant differences (p < 0.05) across positions, tactical systems, and match outcomes. Central defenders consistently showed higher values of Degree Centrality and Degree Prestige across most systems and outcomes, highlighting their structural importance. In contrast, strikers and wingers displayed greater Proximity Prestige in the 1-4-3-3 and 1-3-4-3, reflecting their offensive positioning. Match outcome analysis indicated that wingers had significantly higher Degree Prestige in won matches compared to losses. Overall, results show that micro-level network metrics vary meaningfully by position and context, underscoring the importance of interpreting them cautiously. Despite the novelty of this study, focusing on the initial tactical systems without capturing within-match adjustments may condition the generality of the results. Coaches and practitioners should account for tactical and outcome-related variations when applying network analysis to optimise team dynamics.engmatch analysissoccernetwork analysisperformance analysisnew technologiesjournal article10.3390/app152111513