Dutch cyclist Dylan Groenewegen won today's final stage. How did our model perform today? We saved our best for last, as you'll see below.
- Stage 21: 2h 25' 39" (actual), 2h 25' 50" (prediction), 00' 11" slow (0.13% error)
I never cease to be amazed by elite athletes. A total of 167 cyclists finished the Tour de France. I would be hard-pressed to finish a long flat stage during daylight hours. As for those grueling mountain stages, forget it. I need more time in the gym! My model estimates energy burn, i.e. internal energy burn with an average efficiency of about 20% and not just energy output needed to power the bike. During the entire race about 115,000 Calories could have been burned. Published cyclists' data may be below that number, but an estimate has to be made of internal energy efficiency. Our published papers on Tour de France modeling cite sources that are consistent with our energy estimates. The point is that a LOT of energy is burned during the three-week race. At 550 Calories apiece, those 115,000 Calories amount to nearly 210 Big Macs. That averages to 10 Big Macs per stage! I don't recommend eating Big Macs before cycling, but it does give you some idea of how much energy those cyclists burn each day. You may have heard that 3500 Calories matches the energy content in a pound of fat. That's roughly true, but you may have to burn about twice the Calories to get a pound of fat off because of the complicated way the body converts energy. Either way you think about it, 115,000 Calories represent one or two bowling balls of fat weight. No wonder elite cyclists stay in such great shape. Their job is a wonderful form of exercise!
I once again thank rising high-school senior Ryan Wainer from New York for his work this year. He acquired all the terrain data, which led to a successful set of predictions. How successful? We had one bad prediction with Stage 5 (9.24% error) and five good-a-decade-ago-but-want-to-do-better-today predictions in the error range of 4% - 8%. But that leaves 15 predictions to better than 4%, 11 of which were better than 2%. Five of those 11 were better than 1%, including our best prediction today. A nice way to end!