Purpose:This 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.Addition-ally,this study aimed to assess the differences between faster and slower sprinters in key sprint variables that have not been assessed in previous work.Methods:Velocity-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 (r),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.Results:Modelled 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 r (p ＜ 0.001),and no significant difference was found for vLoss (p =0.085).Conclusion:Coaches 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.