## Fast climb fast analysis Vuelta Stage 16

According to the estimates, Contador and Froome were shockingly fast. The remainder of the contenders fell inline with what we’ve been seeing so far.

input data courtesy of @ammattipyoraily

## 2014 Vuelta Stg 14 and 15 Performance Analysis

Adding stage 14 and 15 into the analysis the power numbers reinforce the impression of a cautious race. Typically, the deeper that riders go trying to push the limits of their ability the more likely we are to see some erratic performances. With 5 finishing climbs completed, the estimates have a distinct lack of of this erraticness. Instead, the power estimates are falling incredibly neatly on a power duration curve with a large amount of clustering any given climb. This is not entirely surprising considering the definitive climb of the race (Ancares) does not come until stage 20. Waiting for stage 20 however, will surely leave some wondering what if.

As for the pVAM, the longer climbs according to the model have not been particularly impressive. Again, the short climbs are in a faded color as the model validity may be fairly question at these very short durations.

## Cyclists needed for cycling performance study

We are currently recruiting participants for a performance modelling study.

Requirements for participation are that you race and train with a power meter.

Please contact Dr Jonathan Baker; jrb07@aber.ac.uk for more information.

## 2014 Vuelta Brief Analysis through Stage 11

With 3 finishing climbs done and analyzed the power duration curve is starting to take shape.

Overall, the performances have been more clustered than spread with the exception of Froome and Valverde falling off the pace on stage 9. Estimate wise, stage 11, the longest of the three was also the most pedestrian but road surface and tactics may have also been a larger than usual factor.

In terms of the pVAM model, only stage 11 is long enough to fall within the range that the model was intended for. I did leave the others stages in but I faded them out a bit as a reminder to not get to confident about the model result there.

## Uncanny resmemblances

http://www.ncbi.nlm.nih.gov/pubmed/19777251

as pointed out before the WKO4 model appears to be made up of the stringing together of 4 models that based on the distribution of their residuals function like a pmax model, a CP1-10 model, a CP3-30 model, and something that slopes down to cross the measured curve at the 45-60 minute range. the overlay of the CP models and the WkO4 model is previously illustrated in this post http://veloclinic.tumblr.com/post/72305824574/for-educational-purposes-only-post-contains-only