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Orioles Extend Funding for AI-Powered Pitching Analytics as Researchers Expand to New Sports

The University of Waterloo's PitcherNet, which analyzes pitcher mechanics using low-resolution video, is now being adapted for hockey, basketball, and batting applications.

The Orioles partnered with the University of Waterloo in Ontario to develop artificial intelligence technology that can monitor pitchers with low-resolution video. (Photo courtesy of the University of Waterloo)
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Overview

  • PitcherNet, developed by University of Waterloo researchers, uses AI to analyze pitcher performance and mechanics from standard broadcast and smartphone video.
  • The Baltimore Orioles initially commissioned the system to address analytics gaps for away, minor league, and college games lacking high-cost stadium camera systems.
  • The AI system creates 3D pitcher avatars to measure metrics like velocity and release point, helping improve performance and reduce injury risks.
  • The Orioles and Waterloo have committed to funding PitcherNet for another year as it continues to be actively used for player analysis.
  • Researchers are now piloting the technology's expansion to other sports, such as hockey and basketball, and exploring its application to baseball batting analytics.