For a myriad of reasons, I've not written a blog post in quite some time. But with the Tour de France commencing this Saturday, it's time to get back to blog writing! The world's most famous bike race starts in the far western part of France, in Brest. My University of Lynchburg research student, Noah Baumgartner, and I have our model ready for stage-winning time predictions. We take terrain data and the laws of physics, plus some measured parameters associated with cycling, and then toss them all into a computer to predict the time needed for the best of the best to complete each stage. We don't focus on a single cyclist, but instead focus on what the best cyclist for a given stage could do.
A prior commitment has me out of town over the next three days, which means I won't be able to watch the first two stages. I'll write more detailed blog posts when I return next week. For now, I'll give our predictions for the first three stages.
- Stage 1: 4h 36' 19" (prediction)
- Stage 2: 4h 17' 14" (prediction)
- Stage 3: 4h 07' 58" (prediction)
As has always been the case for my Tour de France work, the science is what interests me the most. Studying the race, including a post-race analysis, will provide me with lots of insights into elite cycling. Blog post predictions in this space have always been an element of fun that I've infused into my scientific work. We don't know exactly what weather will be like on a given stage, we aren't privy to teams' strategies, knowing when riders need to relieve themselves isn't on our radar screen, and we can't predict crashes. The stages we really miss are the ones that teach us the most.
I'll be back on Monday to watch Stage 3, though I may have to sneak a peek while I'm away to see how our predictions fared on the first two stages. Enjoy the 108th edition of the Tour de France!
No comments:
Post a Comment