PREDICTION OF 100 METERS SPRINT PERFORMANCE BASED ON FIELD TEST

ABSTRACT Introduction: The 100-meter dash (100 m) event holds particular appeal. Coaches and researchers seek to understand the determinants of performance in this task. Although information has been produced over the years, it is not fully applied by coaches who generally assess the success of employed training methods through objective field tests, such as 60 m dash test performance. Objective: Investigate 100 m performance based on 60 m performance. Methods: Two hundred and forty six men and 153 women divided into two subgroups were evaluated for estimation (Fvalidation; n=123 and Mvalidation; n=204) and validation of predictive models (Fcross-validation; n=30 and Mcross-validation; n=42) for 100 m dash performance (time take to cover 100 m). Partial time was measured based on the 100 m distance marked previously every 10 meters from the starting line on both sides of the track. The predictive models were based on the interval in the 60 meters with a time interval of 10-10 m. Results: Magnitude of correlation was very high. High coefficients of determination and differences of no statistical significance (p <.001) were found between the criteria and predicted values. The predictive equations presented constant error values below 0.001s; total absolute error of 0.12s; 0.10s for Mvalidation and Fvalidation, respectively, and 1.13% and 0.85% of total relative error for Mvalidation and Fvalidation, respectively. Bland-Altman analysis showed an increase in the level of concordance between the criteria and predicted values of Fvalidation and Mvalidation. Similar responses were found when the proposed models were applied to Fcross-validation and Mcross-validation. Conclusion: The estimation models were able to accurately predict 100 m performance based on 60 m performance. Level of evidence: II; Diagnostic studies - Investigating a diagnostic test.