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, O2max 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 (MMP2000 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 MMP2000 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.
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Published online: November 30, 2022
Accepted: November 28, 2022
Received in revised form: November 16, 2022
Received: July 10, 2022
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