Accuracy of indirect estimation of power output from uphill performance in cycling
http://journals.humankinetics.com/A...umentItem/Millet_IJSPP_2013_0320-in press.pdf
ABSTRACT 
Purpose: To use cycling powermeters (Pmes) to evaluate the accuracy of commonly used models for 
estimating uphill cycling power (Pest). More specifically experiments were designed to understand 
the influence of wind speed and climb steepness on accuracy of Pest. We hypothesized that (1) the 
random error in Pest is largely influenced by the windy conditions; (2) the bias is diminished in 
steeper climbs; and (3) windy conditions induce larger bias in Pest. Methods: Sixteen well-trained 
cyclists performed 15 uphill cycling trials (range: length 1.3 – 6.3 km; slope 4.4-10.7%) in a random 
order. Trials included different riding position in a group (lead or follow) and different wind speeds. 
Pmes was quantified using a powermeter and Pest was calculated using methodology used by 
journalists reporting on the Tour de France. Results: Overall, the difference between Pmes and Pest 
was -0.95% (95%CI: -10.4%; +8.5%) for all trials and 0.24% (-6.1%; +6.6%) in conditions without wind 
(< 2 m.s-1
). The relationship between percent slope and the error between Pest and Pmes was 
considered trivial. Conclusions: Aerodynamic drag (affected by wind velocity and orientation, frontal 
area, drafting and speed) is the most confounding factor. The mean estimated values are close to 
the PO values measured by powermeters, but the random error is between ±6% and ±10%. 
Moreover, at the POs (>400 W) produced by professional riders, this error is likely to be higher. This 
observation calls into question the validity of releasing individual values without the reporting of the 
range of random errors.