Abstract
In baseball, heat maps, which visualize a batter’s ability across regions in and around the strike zone, play an important role in baseball commentary and scouting reports. We represent the stochastic process underlying these heat maps as a spatial Gaussian field with isotropic covariance. Spatial interpolation (kriging) relies on the assumption of a known covariance function, but in reality the parameters of the covariance are typically estimated from the data. Our simulation study, based on a known covariance function, helps to understand and explain the spatial dependence of the process and allows us to produce improved heat maps.
Acknowledgments
We wish to thank the Editor-in-Chief, Associate Editor and two anonymous reviewers for their constructive suggestions that helped improve the presentation of this paper.
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©2015 by De Gruyter
Articles in the same Issue
- Frontmatter
- Research Articles
- A stochastic rank ordered logit model for rating multi-competitor games and sports
- The implied volatility of a sports game
- Modeling spatial batting ability using a known covariance matrix
- Rethinking the FIFA World Cup™ final draw
- Playing on artificial turf may be an advantage for Norwegian soccer teams
Articles in the same Issue
- Frontmatter
- Research Articles
- A stochastic rank ordered logit model for rating multi-competitor games and sports
- The implied volatility of a sports game
- Modeling spatial batting ability using a known covariance matrix
- Rethinking the FIFA World Cup™ final draw
- Playing on artificial turf may be an advantage for Norwegian soccer teams