Relationships between training dose and record power outputs in professional road cyclists: insights and threats to validity

Abstract

Testing short-term (4–8 weeks) correlations between training dose and performance in professional road cyclists can help improve their training and performance. Multilevel mixed-modeling was used to correlate training dose (Time, Edwards’ Trimp-eTRIMP, Training Stress Score-TSS, time spent in power output zones-Z1, Z2, Z3, Polarization Index-PI) and Record Power Output (RPO) over 1 minute (RPO1), 5 (RPO5), 20 (RPO20), and 40 minutes (RPO40) across four different time periods: training dose of the previous month with RPOs of the subsequent month (Monthly-analysis); training dose of the 8 weeks preceding All, Grand tours, One-day races with RPOs of these races. In Monthly-analysis, small positive relationships between all the training dose parameters, except for PI, and RPO1, RPO5, RPO20, RPO40 were found (p ≤ 0.001). In Grand tours analysis, Z3 showed a positive association with RPO40 (r: 0.45; p = 0.007, moderate) and was positively related to RPO1 and RPO5 (r between 0.32 and 0.34; p = 0.053–0.059, moderate). PI was small positively related to RPO1 (r = 0.29, p = 0.076, small). In One-day races analysis, eTRIMP was positively related to RPO5 (r = 0.30, p = 0.035, moderate), Z1 negatively related to RPO40 (r = -0.31, p = 0.031, moderate), PI positively related to RPO5 (r = 0.24, p = 0.068, small) and Z2 was negatively related to RPO20 (r = -0.29, p = 0.051, small). A certain degree of responsiveness to training dose exists in professional road cyclists. To improve RPOs an appropriate preparation pattern seems to be increasing high intensity training for Grand Tours and fostering high intensity and overall training load (eTRIMP and TSS) in a more polarized-fashion for one-day races. Systematic and precise data collection during training and racing is highly advocated.

Utility of the W´BAL model in training programme design for masters cyclists

“…For example, world class cyclists preparing for the Giro d'Italia adopted a pyramidal intensity distribution with an increase in high-intensity volume and polarization index in race weeks (Gallo et al, 2022). In addition, a positive effect of training on power output suggests that a certain degree of responsiveness to training persists in professional cyclists (Gallo et al, 2023). However, questions remain with respect to optimal training regimes.…”