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Modeling spatial batting ability using a known covariance matrix

Author

Listed:
  • Cross Jared
  • Sylvan Dana

    (Hunter College of the City University of New York – Mathematics and Statistics, New York, NY, USA)

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.

Suggested Citation

  • Cross Jared & Sylvan Dana, 2015. "Modeling spatial batting ability using a known covariance matrix," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(3), pages 155-167, September.
    • Handle: RePEc:bpj:jqsprt:v:11:y:2015:i:3:p:155-167:n:3
    DOI: 10.1515/jqas-2014-0089
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    References listed on IDEAS

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    1. Shortridge Ashton & Goldsberry Kirk & Adams Matthew, 2014. "Creating space to shoot: quantifying spatial relative field goal efficiency in basketball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(3), pages 1-11, September.
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