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Inequality and distribution of injury burden in elite basketball: a cohort study using complementary analytical
Javier Pérez-Murillo1,2, Pedro Cotolí-Suarez1, Borja Ricart-Luna1,3,4
1Alqueria Lab Department, Valencia Basket, Valencia, Spain.
Background:
Injury epidemiology in basketball has traditionally focused on incidence and injury type, with limited attention to how injury burden is distributed within teams. Understanding the distribution of time-loss may provide a complementary perspective on the impact of injuries on player availability. The aim of this study was to describe injury epidemiology and to analyze the distribution and inequality of injury burden during a competitive season in elite basketball players.
Methods:
A retrospective longitudinal observational study was conducted using routinely collected clinical data from a professional basketball club during the 2024-2025 season. Forty players (male and female) from four teams were included. Injury incidence was calculated as injuries per 1000 athlete-days. Injury burden was defined as total days lost. Distribution of injury burden was assessed using Lorenz curves, the Gini coefficient, and Pareto analysis. Multilevel modelling and clustering were applied as exploratory, hypothesis-generating analyses of player-level variability. Non-parametric tests (Mann-Whitney U and Kruskal-Wallis) and chi-square tests were used for group comparisons.
Results:
A total of 50 injuries were recorded, accounting for 1369 days lost, corresponding to an overall incidence of 1.70 injuries per 1000 athlete-days (95% CI: 1.26-2.24). Injury burden showed a moderate-to-high degree of inequality (Gini = 0.61; 95% CI: 0.45-0.70). A relatively small proportion of injuries accounted for a substantial share of total time-loss: 5 injuries (10%) explained 50% of the burden, 18 injuries (36%) explained 80%, and 28 injuries (56%) explained 90%. No consistent relationship was observed between injury incidence and burden across teams.
Conclusions:
Injury burden in elite basketball appears to be unevenly distributed, with a limited number of injuries contributing substantially to total time-loss. These findings suggest that assessing the distribution of injury burden, rather than relying solely on incidence, may provide additional, preliminary insight into injury impact. However, given the observational design and limited sample size, these findings should be interpreted with caution.
