<![CDATA[The sprint start is a critical determaint of performance because it strongly influences an athlete’s ability to generate rapid acceleration during the initial phase of a sprint. This study aimed to evaluate the sprint start technique of adolescent athletes from the Golden Athletics Club, Surabaya, through video-based biomechanical analysis. A descriptive quantitative design with an observational approach was employed. Ten active 100-meter sprinters aged 15–16 years, consisting of eight males and two females, were recruited using total sampling. Kinematic analysis was conducted using the Kinovea software to assess four variables: anterior knee angle, posterior knee angle, trunk inclination, and first-step length. Intra-rater reliability demonstrated percentage errors below 5% for all variables, indicating excellent measurement consistency. The findings showed that most athletes demonstrated anterior knee angles within the fair-to-good range, whereas posterior knee angles generally remained below the recommended biomechanical range. Excessive trunk inclination was observed in most participants, suggesting suboptimal body positioning during block clearance. First-step length ranged from 81.0 to 102.5 cm, with most athletes demonstrating acceptable performance. Overall technique scores ranged from 43.75% to 75.00%; one athlete was classified as good, four as fair, and five as poor. These findings indicate that sprint start technique among the participating athletes requires further improvement, particularly in lower-limb positioning and trunk alignment, to enhance horizontal force production during the acceleration phase. Kinovea-based video analysis provides a practical and accessible method for evaluating sprint start mechanics in field-based training settings. Nevertheless, because this study involved a small sample from a single athletics club and did not include sprint performance outcomes, the findings should be interpreted within the context of the study and should not be generalized to broader athlete populations.]]>
