Professional sports teams pour millions of dollars into data analytics, using advanced tracking systems to study every sprint, pass, and decision on the field. The results of that analysis, however, are industry secrets, making many sports difficult for researchers to study.
Now, two University of Waterloo researchers, Dr. David Radke and Kyle Tilbury, are using AI to level the playing field.
By tapping into Google Research Football’s reinforcement learning environment, the researchers developed a system that can simulate and record unlimited soccer matches. To get things started, they generated and saved data from 3,000 simulated soccer games, resulting in a rich and complex dataset of passes, goals, and player movements for researchers to study.
Read the full story from Waterloo News to learn more.