Two Cheriton alumni, David Radke and Kyle Tilbury, are using AI to make it easier for researchers to unlock sports insights— which were previously reserved for pro-teams.
By leveraging the Google Research Football’s reinforcement learning environment, the duo created a system that can simulate and record unlimited soccer matches. 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.
“While researchers have access to a lot of data about episodic sports like baseball, continuous invasion-game sports like soccer and hockey are much more difficult to analyze,” said Radke, a recent Waterloo PhD graduate in computer science and currently a senior research scientist for the NHL’s Chicago Blackhawks.
“While the AI-generated players might not exactly play like Lionel Messi, the simulated datasets they generate are still useful for developing sports analysis tools.”
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