Going top shelf with AI to better track hockey data

Hockey game Waterloo researchers get an assist from AI in identifying hockey players with greater accuracy and speed Researchers from the University of Waterloo got a valuable assist from artificial intelligence (AI) tools to help capture and analyze data from professional hockey games faster and more accurately than ever before, with big implications for the business of sports. The growing field of hockey analytics currently relies on the manual analysis of video footage from games. Professional hockey teams across the sport, notably in the National Hockey League (NHL), make important decisions regarding players- careers based on that information. -The goal of our research is to interpret a hockey game through video more effectively and efficiently than a human,- said Dr. David Clausi, a professor in Waterloo's Department of Systems Design Engineering. -One person cannot possibly document everything happening in a game. Hockey players move fast in a non-linear fashion, dynamically skating across the ice in short shifts. Apart from numbers and last names on jerseys that are not always visible to the camera, uniforms aren-t a robust tool to identify players - particularly at the fast-paced speed hockey is known for.