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...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.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.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(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.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 andτ(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.展开更多
基金the Irish Research Council for financially supporting this research。
文摘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.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.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(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.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 andτ(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.
