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Objectives and questions: Gait analysis has become an increasingly valuable tool in the understanding and prevention of various types of injuries. The integration of AI in gait analysis enables enhanced data processing and predictive modeling. Basketball is often associated with a wide range of injuries due to its high impact nature, dynamic movements, and frequent changes in direction. The primary aim of this investigation was to describe the magnitude of asymmetries of common variables during walking among elite basketball athletes and identify gender based differences.

Material and methods: 23 elite basketball players were enrolled in this study including 10 female and 13 male players. For the gait analysis the Orthelligent^©VISION system was used. Participants performed three walking cylcles in the frontal and lateral plane as well as stair climbing/descending. The following parameters were generated: gait symmetry, cadence (steps per minute), pace, step width, step time, step length, stance phase, double support phase, gait variability, shoulder angle, projected leg axis and foot alignment. Continuous variables were summarized as mean ± standard deviation, and differences between men and women were assessed using independent-samples t-tests at a two-sided significance level of 0.05. Dichotomous variables were described using absolute and relative frequencies; all analyses were exploratory.

Results: Both genders demonstrated excellent gait symmetry across all planes (frontal: 96% female vs. 96% male; lateral: 96% vs. 95%; stairs: 93% vs. 96%). Female athletes showed significantly higher cadence compared to males in the frontal plane (116 vs. 101 steps/min; p=0.005), lateral plane (100 vs. 92 steps/min; p=0.023), and stairs (103 vs. 90 steps/min; p=0.023). Conversely, males exhibited significantly longer step times across all planes. A longer stance phase was observed in males on the left side in the frontal plane (56% vs. 52%; p=0.020). The projected leg axis tended toward valgus alignment in females and varus alignment in males, with significant differences in the frontal plane and during stair analysis. Both sexes showed greater external rotation of the right foot compared to the left in the frontal plane and during stair assessment.

Discussion and conclusions: Elite male and female basketball players demonstrated overall excellent gait symmetry across all movement planes. However, significant gender-specific differences were identified in certain gait parameters, such as cadence, step time, stance phase and limb alignment. These findings indicate distinct gender-related gait characteristics despite symmetrical walking patterns, highlighting the potential value of AI-based gait analysis for individualized injury risk assessment, prevention strategies, and personalized rehabilitation in elite basketball athletes.