Critical velocity (CV) represents, theoretically, the highest velocity that can be sustained without fatigue. The aim of this study was to compare CV computed from 5 mathematical models in order to determine which CV estimate is better correlated with 1-hour performance and which model provides the most accurate prediction of performance. Twelve trained middle- and long-distance male runners (29 +/- 5 years) performed 3 randomly ordered constant duration tests (6, 9, and 12 minutes), a maximal running velocity test for the estimation of CV, and a 1-hour track test (actual performance). Two linear, 2 nonlinear, and 1 exponential mathematical models were used to estimate CV and to predict the highest velocity that could be sustained during 1 hour (predicted performance). Although all CV estimates were correlated with performance (0.80 < r < 0.93, p < 0.01), it appeared that CV estimated from the exponential model was more closely associated with performance than all other models (r = 0.93; p < 0.01). Analysis of the bias +/- 95% interval of confidence between actual and predicted performance revealed that none of the models provided an accurate prediction of the 1-hour performance velocity. In conclusion, the estimation of CV allows us to rank middle- and long-distance runners with regard to their ability to perform well in long-distance running. However, no models provide an accurate prediction of performance that could be used as a reference for coaches or athletes.
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