The 104th edition of the race will see the Tour carry out a pilot machine learning program that will aim to predict the likelihood of various race scenarios. For example, the data could help researchers glean whether the peloton (the main pack of riders) will catch the breakaway riders at certain stages of the race. Using GPS transponders, installed under the saddles of each bike, a whopping 3 billion data points will be collected throughout the 21 stages of the Tour. These insights will be combined with external data (such as the course gradient and weather conditions) to bring viewers a range of breaking stats, including live speed and the location of individual riders, distance between riders, and composition of groups within the race. The hub for this information will be a cloud-based data centre, which will relay stats to broadcasters, allowing them to tell you even more about your favorite teams or riders.

The Kentucky Derby is dubbed as "the most exciting two minutes in sports." By the same token, it also may be the most difficult two minutes in sports to predict. That's why artificial intelligence is now being used to handicap the annual race. Churchill Downs, Silicon Valley-based Unanimous A.I. and TwinSpires have combined efforts to produce some of the most accurate predictions that racing has ever seen. In fact, last year Unanimous A.I. correctly predicted the top-four Derby finishers (the Superfecta), in order.