PitcherNet helps researchers throw strikes with AI analysis

University of Waterloo researchers have developed new artificial intelligence (AI) technology that can accurately analyze pitcher performance and mechanics using low-resolution video of baseball games. The system, developed for the Baltimore Orioles by the Waterloo team, plugs holes in much more elaborate and expensive technology already installed in most stadiums that host Major League Baseball (MLB), whose teams have increasingly tapped into data analytics in recent years. Waterloo researchers convert video of a pitcher's performance into a two-dimensional model that PitcherNet's AI algorithm can later analyze. Those systems, produced by a company called Hawk-Eye Innovations, use multiple special cameras in each park to catch players in action, but the data they yield is typically available to the home team that owns the stadium those games are played in. To add away games to their analytics operation, as well as use smartphone video taken by scouts in minor league and college games, the Orioles asked video and AI experts at Waterloo for help about three years ago.