Aerobic and anaerobic indices contributing to track endurance cycling performance

Summary

A group of 18 male high performance track endurance and sprint cyclists were assessed to provide a descriptive training season specific physiological profile, to examine the relationship between selected physiological and anthropometric variables and cycling performance in a 4000-m individual pursuit (IP₄₀₀₀) and to propose a functional model for predicting success in the IP₄₀₀₀. Anthropometric characteristics, absolute and relative measurements of maximal oxygen uptake ($\dot VO_{2max}$), blood lactate transition thresholds (Th _1a- and Th _an,i), $\dot VO_2$ kinetics, cycling economy and maximal accumulated oxygen deficit (MAOD) were assessed, with cyclists also performing a IP₄₀₀₀ under competition conditions. Peak post-competition blood lactate concentrations and acid-base values were measured. Although all corresponding indices of Th_1a- and Th _an,i occurred at significantly different intensities there were high intercorrelations between them (0.51–0.85). There was no significant difference in MAOD when assessed using a 2 or 5 min protocol (61.4 vs 60.2 ml·kg⁻¹, respectively). The highest significant correlations were found among IP₄₀₀₀ and the following: $\dot VO_{2max}$ (ml·kg^−2/3·min⁻¹; r=−0.79), power output at lactate threshold ($\dot W_{th_{1a} }$) (W; r=−0.86), half time of $\dot VO_2$ response whilst cycling at 115% $\dot VO_{2max}$ (s; r=0.48) and MAOD when assessed using the 5 min protocol (ml·kg⁻¹; r=−0.50). A stepwise multiple regression yielded the following equation, which had an r of 0.86 and a standard error of estimate of 5.7 s: IP₄₀₀₀ (s) = 462.9 − 0.366 × 0.306 × ($\dot W_{th_{1a} }$) − 0.306 × (MAOD) −0.438 × ($\dot VO_{2max}$) where $\dot W_{th_{1a} }$is in W, MAOD is in ml·kg⁻¹ and $\dot VO_{2max}$ is in ml·kg⁻¹·min⁻¹. These results established that these male high performance track endurance cyclists had well-developed aerobic and anaerobic energy systems with $\dot VO_{2max}$, Th _1a and MAOD being primary important factors in a IP₄₀₀₀. Therefore, it is suggested that these variables should be optimally trained and routinely monitored when preparing track endurance cyclists for competition.