The thin edge of the wedge: Accurately predicting shot outcomes in tennis using style and context priors
The aim of this paper is to discover patterns of player movement and ball striking (short-and long-term shots, and shot combinations) in tennis using HawkEye data which are indicative of changing the probability of winning a point. This is a challenging task because: i) behavior can be unpredictable, ii) the environment is dynamic and the output state-space is large and iii) examples of specific interactions between agents may be limited or non-existent (player A may not have interacted with player B). However, by using a dictionary of discriminative patterns of player behavior, we can form a representation of a players style, which is interpretable latent factors that allows us to personalize interactions between players based on the match context (opponent, match-score).
This approach allows us to perform superior point predictions, and to understand how points are won by systematically creating and exploiting spatiotemporal dominance.
© Copyright 2016 MIT Sloan Sports Analytics Conference 2016. All rights reserved.
|Subjects:||tennis high performance sport analysis competition performance technique auxiliary device software perception prognosis movement movement velocity movement precision|
|Notations:||sport games technical and natural sciences|
|Published in:||MIT Sloan Sports Analytics Conference 2016|
|Document types:||congress proceedings