Abstract

PurposeThis study aimed to determine the accuracy of a 4 split time modelling method to generate velocity-time and velocity-distance variables in elite male 100-m sprinters and subsequently to assess the roles of key sprint parameters with respect to 100-m sprint performance. Additionally, this study aimed to assess the differences between faster and slower sprinters in key sprint variables that have not been assessed in previous work. MethodsVelocity-time and velocity-distance curves were generated using a mono-exponential function from 4 split times for 82 male sprinters during major athletics competitions. Key race variables—maximum velocity, the acceleration time constant (τ), and percentage of velocity lost (vLoss)—were derived for each athlete. Athletes were divided into tertiles, based on 100-m time, with the first and third tertiles considered to be the faster and slower groups, respectively, to facilitate further analysis. ResultsModelled split times and velocities displayed excellent accuracy and close agreement with raw measures (range of mean bias was –0.2% to 0.2%, and range of intraclass correlation coefficients (ICCs) was 0.935 to 0.999) except for 10-m time (mean bias was 1.6% ± 1.3%, and the ICC was 0.600). The 100-m sprint performance time and all 20-m split times had a significant near-perfect negative correlation with maximum velocity (r ≥ –0.90) except for the 0 to 20-m split time, where a significantly large negative correlation was found (r = –0.57). The faster group had a significantly higher maximum velocity and τ (p < 0.001), and no significant difference was found for vLoss (p = 0.085). ConclusionCoaches and researchers are encouraged to utilize the 4 split time method proposed in the current study to assess several key race variables that describe a sprinter's performance capacities, which can be subsequently used to further inform training.

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