Abstract Background Acute injuries are common in rugby and threaten both player health and career longevity. Previous studies often focused on isolated risk factors, while limited research has comprehensively examined the interplay of physiological, environmental, and situational variables. Methods Study conducted a cohort study of 40 elite male players from the Tianjin Rugby Team, monitoring 575 match exposures across 2.5 consecutive seasons (2022–2025). Acute injuries were defined according to international consensus criteria and verified by medical staff. Spatiotemporal distributions (seasonal variation, match stage, playing position, and body site) were analyzed using chi-square and logistic regression. Multivariate models were applied to identify independent risk factors including demographic, training, and environmental variables. Results A total of 143 acute injury events were recorded, with bone and joint injuries most prevalent (48.2%) and the majority classified as moderate-to-severe (78.3%). Injury rate rose significantly to 1.84 per 1,000 player-hours in 2024/25 vs. 1.83 in 2022/23 and advanced competition stages (OR for finals = 7.06 vs. group stage, p < 0.001). Forwards exhibited higher risk than backs (OR = 1.51), and injuries most frequently involved the head/face, upper limbs, and lower limbs. Multivariate regression identified excessive training load (OR = 3.78), extreme temperatures (OR ≈ 6.5–6.8), elite athletic level (OR = 1.84), prior injury history (OR = 5.98), poor sleep quality (OR = 5.64), and mild fatigue (OR = 2.48) as significant predictors. Conclusions Acute injury risk in rugby demonstrates clear spatiotemporal patterns and is strongly influenced by both individual and environmental factors. The model developed provides a practical basis for targeted prevention strategies, including load management, environmental adaptation, and individualized recovery protocols. These findings may assist coaches and medical teams in optimizing training and competition management, while future research should expand cohorts and integrate
Xiaodong et al. (2025) studied this question.