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Looking at spacings to assess streakiness

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  • Albert Jim

    (Bowling Green State University-Mathematics and Statistics Bowling Green, Ohio, USA)

Abstract

There is much interest in studying the hot hand behavior of individuals and teams in sports. We collect success/failure data for each of the hitters in a particular baseball season, focusing on the spacings or number of at-bats between consecutive successes. Consistent and streaky models are defined on the basis of the underlying geometric probabilities and a Bayes factor statistic is developed to compare the two models. By looking at the ensemble of test statistics over all players, we see if the patterns of streakiness differ from what one would predict from a consistent hitting model. An interesting observation from this study is the pattern of streakiness depends on how one defines a success in a plate appearance.

Suggested Citation

  • Albert Jim, 2013. "Looking at spacings to assess streakiness," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(2), pages 151-163, June.
    • Handle: RePEc:bpj:jqsprt:v:9:y:2013:i:2:p:151-163:n:3
    DOI: 10.1515/jqas-2012-0015
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    References listed on IDEAS

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    1. Albert James, 2006. "Pitching Statistics, Talent and Luck, and the Best Strikeout Seasons of All-Time," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(1), pages 1-32, January.
    2. Tae Young Yang, 2004. "Bayesian binary segmentation procedure for detecting streakiness in sports," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 627-637, November.
    3. Albert Jim, 2008. "Streaky Hitting in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 4(1), pages 1-34, January.
    4. Klaassen F. J G M & Magnus J. R., 2001. "Are Points in Tennis Independent and Identically Distributed? Evidence From a Dynamic Binary Panel Data Model," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 500-509, June.
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    Cited by:

    1. Gerber Eric A. E. & Craig Bruce A., 2021. "A mixed effects multinomial logistic-normal model for forecasting baseball performance," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(3), pages 221-239, September.

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