Discovery Sports turned to Amazon Web Services to deliver fan engagement experiences for the upcoming UCI Track Champions League.

AWS will provide a cloud infrastructure for the competition, and become the official provider of cloud, artificial intelligence, machine learning and deep learning for Discovery Sports Events as a whole.

Fan engagement for the Track Champions League will include a new UCI Track Champions League app, competition information and race statistics. The new application will aim to offer fans a connected experience to develop communities around the competition.

For statistics, Amazon Kinesis will ingest and process live streaming data from sensors on the track, bikes and runners, which will then be analyzed with AWS analysis and machine learning capabilities to provide statistics such as as bike speed, running position, pedal cadence (i.e. revolutions per minute), rider power output in watts, timing and rider biometrics (e.g. heart rate, calories burned) . These statistics will then be provided to fans via broadcasts and the app.

In addition to providing real-time data on runner performance and race statistics, Discovery Sports Events will use Amazon SageMaker to develop predictive information on race and championship results.

The UCI Track Champions League kicks off in Mallorca, Spain, in November, and consists of six rounds of racing taking place in Spain, France, Lithuania, the UK and Israel, which aim to give an all-round narrative. throughout the year to sport outside the Olympics. and the major annual races.

Kathrin Buvac, Vice President of Business Development at Amazon Web Services, said, “Sports are a great way to bring technologies like machine learning and data to life in a way that sports fans around the world whole people can understand and be enthusiastic.

“AWS and Discovery Sports Events will help the UCI redefine and innovate track cycling by providing fans with a more connected experience with real-time data on rider performance and race statistics. Imagine that fans could see things like predictive information and the bike speeds of their favorite riders, race positions, pedaling cadences and even biometrics, all from a connected app on their phones.