It's Tour de France Time!

On the eve of the world's most famous bicycle race, I am once again geared up to post my research team's predictions for the Tour de France's stage-winning times.   We model elite cycling using published values of cyclist power output, air drag, tire/road friction, terrain data, and, of course, the laws of physics that constrain us all.  This year's race looks to dazzle those of us who love watching battles in the high mountains.

Stage 1 commences in the Belgian capital of Brussels.  The 194.5-km (120.9-mi) flat stage takes riders west, then south of Brussels, before returning north back into Brussels.  Our prediction for the first stage's winning time is given below.

• Stage 01:  4h 32' 00" (prediction)

My research students here at the University of Lynchburg are Carl Pilat, who worked with me last summer, and Noah Baumgartner, who joined my research team this summer.

As I sports physicist, I want to understand how elite athletes are able to do what they do.  I also want to understand the equipment and playing surfaces they use.  Modeling the Tour de France is about taking something extremely complicated and simplifying it enough that one begins to understand it on a fundamental level.  Sticking our necks out and posting stage-winning times is merely our way of spicing up what we do.  We can never fully know weather conditions, and we're not privy to the various strategies employed by the cycling teams.  And we certainly can't know ahead of time if there will be crashes, delays, protests by fans, interference by fans, cows roaming onto the road, and so on.  Those aren't excuses for bad predictions, just the reality of trying to model something so complex.  We love it when a prediction is nearly spot on, and when our predictions don't fare so well, we are given an opportunity to learn something.  That's one reason why being a scientist is such a delight!