From speed to watts: a physics-based model for estimating power output during professional cycling climbs

Accurate quantification of mechanical power output is fundamental for performance analysis in road cycling. However, access to power meter data is often limited in research and applied contexts. The aim of the present study was to develop and validate a physics-based framework to estimate power outputs in professional cycling with publicly available data.

Performance data from professional cyclists who completed the uphill individual time trial to Peyragudes in the 2025 Tour de France were obtained from publicly available sources. Mean power output was estimated using a mechanical model that accounts for gravitational, aerodynamic, and rolling resistance forces, incorporating rider mass, course characteristics, velocity, and altitude-derived air density. Estimated values were compared with power meter data available from riders' publicly shared activity files.

The comparison across 28 professional cyclists showed a good level of agreement between estimated and measured power outputs (mean absolute error = 14.07 W; Mean absolute percentage error = 3.65%). The model exhibited a small mean bias of -5.43 W where the model slightly underestimated the reported power. Bland-Altman analysis yielded 95% limits of agreement from -36.27 to 25.41 W with 26 of 28 observations within these limits.

These results demonstrate that cycling power during sustained climbing efforts could be approximated using simple externally observable variables. This approach may represent a useful tool for reconstructing performance when direct power meter data are unavailable in professional cycling.