Avaliação dos Correlatos da Ocorrência de Lesões em Jogadores Profissionais de Futebol: Uma Análise de Rede Baseada na Teoria da Complexidade

Abstract

Introduction: Lower limb injuries in football players represent a significant issue in the sports domain, impacting health, performance, and associated costs. Traditional studies on injuries have primarily focused on physical factors; however, the development of Complexity Science has transformed the understanding of this phenomenon, framing it as a multifactorial system encompassing physical, psychological, and contextual factors. Despite the implementation of preventive strategies, injury rates remain high, particularly under conditions of elevated internal training load. Objective: To evaluate correlates of lower limb injuries in injured and non-injured football players. Methods: This time-series study assessed 24 male professional football players (mean age: 27.89 ± 4.69 years), divided into two groups: injured (n = 11) and non-injured (n = 13). Sociodemographic correlates (previous injury, playing position, and lower limb dominance), anthropometric variables (body mass, height, and body mass index), psychological factors (pre-training well-being perception - fatigue, stress, sleep quality, and delayed onset muscle soreness; post-training rating of perceived exertion), and environmental factors (total distance covered and 3D player load) were assessed on a daily or monthly basis. Statistical Analysis: A classical network analysis using a correlation estimator was conducted to identify the network structure and expected influence of factors within each group. Results: A statistically significant age difference was observed between groups (injured group: 29.73 ± 4.76; non-injured group: 26.08 ± 3.71). No significant differences were found between groups in the monthly mean values of the assessed correlates. Network analysis indicated strong associations between RPE and total distance covered (0.924), RPE and stress level (0.944), as well as between stress and sleep quality (0.941). However, both groups exhibited similar network topologies and expected influence indicators. Conclusion: Network analysis revealed comparable topologies and centrality indicators among injured and non-injured players. Future studies should explore additional correlates not assessed in this study to better discriminate the determinants of lower limb injuries in football players.