Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance...

Area of Science:

• Exercise Physiology
• Sports Science
• Performance Analysis

Background:

• Physiological determinants of middle-distance running performance are complex.
• Accurate prediction of race velocity is crucial for training and competition.
• Systems models offer a framework to estimate physiological parameters like maximal velocity (Vmax) and critical velocity (CV).

Purpose of the Study:

• To assess the validity of Vmax estimated by three-parameter models.
• To compare the predictive accuracy of two- and three-parameter models for 800m race performance (V800m).

Main Methods:

• Seventeen trained male runners completed constant velocity tests (CVT), a maximal velocity test, and an 800m time trial.
• Five systems models (two 3-parameter, three 2-parameter) were used to calculate Vmax, CV, and anaerobic running capacity (ARC).
• Model-derived V800m predictions were compared against actual V800m using correlation (r) and bias.

Main Results:

• Vmax estimates from 3-parameter models were significantly lower and poorly correlated with actual Vmax.
• Critical velocity (CV) alone explained 40-62% of the variance in V800m.
• Combining CV with other parameters improved V800m prediction (r=0.83-0.94).
• Three-parameter models showed superior prediction (r=0.93-0.94) and lower bias (0.00-0.04 m/s) for V800m compared to two-parameter models (r=0.83-0.91, bias=0.06-0.20 m/s).

Conclusions:

• Three-parameter systems models demonstrate better predictive value for 800m performance than two-parameter models.
• Despite improved predictive accuracy for 800m, the poor validity of estimated Vmax suggests empirical rather than purely physiological basis.
• Critical velocity is a strong predictor of 800m performance, especially when integrated within a comprehensive model.