Validity Of A Field-based Critical Velocity Test On Predicting 5,000 M Running Performance

Abstract

Measuring and modeling known adaptations to endurance training can be achieved through a variety of physiological parameters. A unique and emerging performance parameter receiving attention is the notion of critical velocity (CV). This concept allows an athlete’s performance to be mathematically modeled based on the relationship that exists between distance and time. PURPOSE: To assess the validity of a field-based CV test on predicting 5,000 m running performance. METHODS: Five runners (VO2peak 60.14 ± 4.96 ml•kg-1•min-1) completed a graded exercise test to determine VO2peak, a CV test to predict performance, and a 5,000 m time-trial. The CV assessment protocol included time-trials of 3,600 m, 2,400 m, and 1,200 m at maximal exertion on a standard 200 m indoor track. Running performance was predicted using the distance-time model where CV was given by the slope and the anaerobic work capacity (D’) was given by the intercept from linear regression analysis of distance covered against time for each of the three time-trials. Statistical significance was determined a priori at p < 0.05. RESULTS: Predicted 5,000 m performance (18.28 ± 4.38 min) and actual 5,000 m performance (18.17 ± 4.07 min) were not significantly different, t(4) = 0.58, p = 0.594, d = 0.26. The mean difference in performance was 0.11 ± 0.42 min [95% LoA, -0.71 min, 0.93 min]. CV (4.59 ± 0.88 m•s-1) was significantly slower than actual 5,000 m velocity (4.73 ± 0.82 m•s-1), t(4) = -3.081, p < 0.05, d = -1.37. The mean difference in velocity was -0.14 m•s-1 ± 0.10 m•s-1 [95% LoA, -0.34 m•s-1, 0.06 m•s-1]. CONCLUSION: The linear distance-time model can be used to predict 5,000 m running performance. This field-based approach allows performance predictions to be made in a relatively short period of time without the need for access to expensive laboratory equipment.