ORIGINAL RESEARCH article
Front. Sports Act. Living
Sec. Elite Sports and Performance Enhancement
Volume 7 - 2025 | doi: 10.3389/fspor.2025.1599319
Optimal body mass normalization of power output for accurate prediction of estimated cycling performance over complex time-trial courses
Provisionally accepted
- Swedish Winter Sports Research Centre, Faculty of Human Sciences, Mid Sweden University, Östersund, Sweden
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Power profiling is widely used in cycling performance analysis, but both absolute and mass-normalized power outputs have limitations as performance indicators, as they neglect external factors such as terrain, wind, aerodynamic drag, and pacing strategy. To address these limitations, this study introduced a numerical method to quantify how external forces acting on the cyclist influence the conversion of power output into race velocity. Thus, the study aimed to enable accurate prediction of cycling performance based on estimated mean power output over complex time-trial courses. Methods: Time-trial performances of five elite-level road cyclist profiles -a sprinter, climber, all-rounder, general classification (GC) contender, and a time trialist -were estimated using the power-duration relationship and previously published normative data. These performance estimates were applied to both simplified hypothetical courses and complex realworld time-trial courses. Optimal mass exponents for the power-to-mass ratio were determined based on the estimated average speeds over the respective course sections, cyclist morphology, and external factors such as gradient and wind velocity. Results: Across two recent Grand Tour individual time-trial courses, stage 21 of the 2024 Tour de France and stage 7 of the 2024 Giro d' Italia, the duration-weighted optimally mass-normalized power output metrics were W/kg 0.6068 and W/kg 0.4891 , respectively. These metrics accurately predicted the estimated performances of the five defined cyclist profiles (R 2 = 0.99 for both). Discussion: The results indicate that the duration-weighted optimal mass exponents for the power-to-mass ratio are course-specific.By deriving optimal mass exponents across various modeled courses and wind conditions, the study was able to precisely quantify the influence of road gradient, headwind speed, and bicycle mass on the conversion of power output relative to body mass into speed. Further research is needed to validate the presented method for determining optimal mass exponents in real-world performance settings.
Keywords: Allometric scaling, critical power, Numerical methods, performance prediction, power-duration relationship, Sports Engineering, time-trial performance
Received: 24 Mar 2025; Accepted: 21 Jul 2025.
Copyright: © 2025 Horvath and Andersson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Erik Petrus Andersson, Swedish Winter Sports Research Centre, Faculty of Human Sciences, Mid Sweden University, Östersund, 831 25, Sweden
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