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.