Predictors of cycling performance success: Traditional approaches and a novel method to assess performance capacity...

This study aimed to investigate predictors of cycling performance in U23 cyclists by comparing traditional approaches to a novel method - the compound score. Thirty male U23 cyclists (N = 30, age 20.1 ± 1.1 yrs, body mass 69.0 ± 6.9 kg, height 182.6 ± 6.2 cm, V̇O_2max 73.8 ± 2.5 mL·kg^-1·min^-1) participated in this study.

Power output information was derived from laboratory and field-testing during pre-season and mean maximal power outputs (MMP) from racing season. Absolute and relative 5-min MMP, 5-min MMP after 2000 kJ (MMP_{2000 kJ}), allometric scaling and the compound score were compared to the race score and podium (top 3) performance during a competitive season.

Positive and negative predictive values were calculated for all significant performance variables for the likelihood of a podium performance.

The absolute 5-min MMP of the field test revealed the highest negative predictive capacity (82.4%, p = 0.012) for a podium performance. The compound score of the 5-min MMP_{2000 kJ} demonstrated the highest positive and average predictive capacity (83.3%, 78.0%, p = 0.007 - respectively). The multi-linear regression analysis revealed a significant predictive capacity between performance variables and the race score (R² = 0.55, p = 0.015).

Collectively the results of the present study reveal that the compound score, alongside absolute power, was able to predict the highest positive and average likelihood for a podium performance. These findings can help to better understand performance capacity from field data to predict future cycling success.