The general aim of the Computational Analysis of Ice Hockey Gameplay project is to develop a system capable of 1) learning the way ice hockey is played and 2) using this knowledge to enhance team performance. More specifically, we are interested in analyzing video from a particular hockey team, automatically detecting play styles, propensities, and habits and then using this information to suggest strategies for improving a team’s performance. Tthis could manifest in a general form (i.e. improving the overall gameplay of team X) or a more specific form (i.e. helping team X exploit weaknesses of team Y so that team X can beat just team Y). Our work draws on ideas from machine learning and machine vision.
David Fleet Faculty
Ryan Lilien Faculty
Vicki Iverson Graduate Student
Matthew Kitching Graduate Student
Derek Kwok Graduate Student
Mansoor Siddiqui Undergraduate Alumnus
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