Evaluating the performance of an ice hockey team using interactive phases of play

This study measures the interaction between two opposing teams in ice hockey by regressing a number of performance measures to a single measure which enables assessment of a team's performance during the course of a game. The notion of ‘phases of play’, whereby players and teams fluctuate through periods of ‘high phase’ and ‘low phase’ during a game, is used as a theoretical underpinning for the research. We also consider ‘relative phase’ that describes the overall interaction between the two teams. Team game data from the 2005/06 National Hockey League season were collected along with data for the games played up to time of research in the 2006/07 season. An optimized binary logistic regression model for both home and away teams was naturally found to model match outcome better than other methods when a team's score was included as a performance variable. This model correctly classified 91% of games as either a win or a loss. Using live match data, these logistic regression models were then used to create phases of play plots of a home team's and away team's performance throughout the progress of a number of games in the 2006/07 season. These scores were smoothed using a Tukey's T4253H smoother to eliminate excess noise in the phases of play plots. It was concluded that the results of this analysis gave an objective, simple and all-round measure of a team's performance which would be a valuable evaluative asset to coaches, the media and spectators.