Face-off Probability is the National Hockey League’s (NHL) first advanced statistic using machine learning (ML) and artificial intelligence. It uses real-time Player and Puck Tracking (PPT) data to show viewers which player is likely to win a face-off before the puck is dropped, and provides broadcasters and viewers the opportunity to dive deeper into the importance of face-off matches and the differences in player abilities. Based on 10 years of historical data, hundreds of thousands of face-offs were used to engineer over 70 features fed into the model to provide real-time probabilities. Broadcasters can now discuss how a key face-off win by a player led to a goal or how the chances of winning a face-off decrease as a team’s face-off specialist is waived out of a draw. Fans can see visual, real-time predictions that show them the importance of a key part of the game.
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