Percorrer por autor "Nunes, Nuno André"
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- Exploring team dynamics through network analysis: A season review of an elite Portuguese soccer teamPublication . Alves, Ricardo; Dias, Gonçalo Nuno Figueiredo; Nunes, Nuno André; Querido, Sérgio; Vaz, VascoSocial 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.
- Network analysis of offensive dynamics in a Portuguese First Division football team: insights from the 2020-2021 seasonPublication . Alves, Ricardo Jorge da Conceição; Dias, Gonçalo Nuno Figueiredo; Querido, Sérgio; Nunes, Nuno André; Vaz, VascoIntroduction: Network analysis has gained increasing attention, as it provides a framework for identifying both collective and individual behaviours within the football teams. Objective: This study aimed to analyse the offensive actions that resulted in shots using network analysis in a Portuguese First Division football team during the 2020-2021 season. Methodology: All 34 matches were coded using Angles® software. Offensive actions were defined as sequences starting with a ball recovery and ending with a shot. Adjacency matrices were constructed for each match, and both macro and micro analytical approaches were employed to examine differences between the two halves of the season. Results: Findings indicated 914 intra-team interactions, with player 14 (midfielder) and player 2 (forward) as key contributors, particularly in micro network metrics such as degree prestige (passes received) and degree centrality (passes made). Statistical analysis revealed no significant differences in network metrics, including density (W = 95, p = 0.0912) and clustering coefficient (W = 112, p = 0.2689), between the season halves. Discussion: These findings offer valuable insights for practitioners seeking in recognizing play patterns and optimizing team dynamics. Identifying key players allows coaches to design targeted training exercises, enhance player roles, and better assess opposition threats and vulnerabilities. Conclusions:Network metrics provides a comprehensive understanding of team dynamics, particularly in identifying key contributors to offensive actions.
- Positional Influence in Football Passing Networks: An Analysis of the Tactical Systems and Match OutcomesPublication . Alves, Ricardo; Dias, Gonçalo Nuno Figueiredo; Nunes, Nuno André; Martins, Fernando Manuel Lourenço; Querido, Sérgio M.; Vaz, VascoThis 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.
- Social network analysis in football: a systematic review of performance and tactical applicationsPublication . Alves, Ricardo; Dias, Gonçalo Nuno Figueiredo; Nunes, Nuno André; Querido, Sérgio M.; Vaz, VascoIntroduction:This systematic review aims to critically examine the application of social network analysis (SNA) in football, with a focus on its contribution to evaluating team performance, tactical behavior, and player interactions. Methods: Following PRISMA guidelines, a comprehensive search was conducted across four databases (PubMed, Scopus, Web of Science, and SPORTDiscus) from January 2017 to October 2024. Results: Fifty-five peer-reviewed studies met the inclusion criteria, addressing network analysis in official men's professional football matches. Data were extracted and summarized regarding methodological quality, network metrics used, tactical context, and practical implications. Discussion: Most studies demonstrated that cohesive network structures, characterized by high density, clustering coefficients, and centrality, are associated with successful team performance. Centrality metrics were frequently used to identify key tactical players, typically central defenders and midfielders. Recent methodological advances included dynamic time-window analysis, pitch-passing networks, and spatial-temporal integration using tracking data. However, there remains an overrepresentation of elite men's football and offensive phases, with limited focus on defensive networks, youth categories, and women's football. SNA offers a powerful framework to decode the complexity of football performance, evolving from static graphs to dynamic, rolesensitive, and context-rich models. Future research should adopt longitudinal designs, multi-layer network approaches, and closer collaboration with practitioners to enhance the operational utility of network insights in coaching and performance analysis.Systematic review registration: https://osf.io/2pe3y