The goal here is to establish baselines of performance and to raise flags when performance exceeds that which may be physiologically possible. Tucker explains:During the Tour, what I'll do ahead of each mountain stage is graphically show you the expected times, and the expected power outputs. Then, after the stage, once the data are in, we can compare each climb to the various predictions, and describe again the insights the performances offer.
Again, I can't stress enough that this is not done with judgment of performance in mind. It's partly because the study of the limits of performance is fascinating, and partly because we can develop informed, insightful opinions on the state of the sport by understanding the power output. I confess, upfront, and will continue to do so as the race develops, that these are imperfect methods, involving estimates and assumptions. Where possible, I will provide actual SRM data to validate the models (or reveal their inaccuracies), and hopefully by the time the Tour rolls into Paris in just under 3 weeks, we'll all be better for it.It is a busy time of year for me, so I will also apologize in advance if I can't keep up with very stage of the race - these long posts obviously draw significant time away from other responsibilities, so no guarantees! I will however guarantee that I'll share brief thoughts and the insights and analysis of others over at our Twitter and Facebook pages, so do follow us there if you would like more frequent, shorter thoughts during this 100th Tour de France.
The power output of course produces the time, and so the first point of analysis is to compare times from one year to the next. If a rider in 2013 produces an ascent of Alp d'Huez that is faster than anything Pantani, Ullrich, Virenque and Armstrong were able to produce given the doping of that era, then it should be pause for concern and some suspicion.Care must always be taken to maintain a stance of innocent until proven guilty (and by extension, what constitutes criteria of guilt), however, closer attention to the metrics of quantitative performance can serve as a useful complement in efforts to manage doping in sport.
This has been an "unpopular" concept because some people assume it to be the equivalent of guilt based on performance - if you are too fast, you must be doping. That's not entirely true, though it would be almost patronizing to say that there isn't an element of truth in it. The reality, as far as I'm concerned, is that in the past, doping exerted such a large effect on performance that it pushed performances beyond what is possible with normal physiology. . .
In time, advances in training, technology and preparation may slowly erode that advantage, but within a narrow period of a few generations, the effect of the doping seen in cycling in the 90s and early 2000s was so large that I don't believe it possible to match doped performances, and so if or when it happens, some very important questions must be asked. Certainly, in the last few years, every Grand Tour has experienced a "slowing down", and the times in the Giro, Tour and Vuelta have been, with one or two exceptions, slower than they were prior to the biological passport's introduction. In 2011, I wrote a piece for the New York Times describing this and since then, the performances have remained slower. Not proof of a clean sport, by any means, but an encouraging sign.