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A Probabilistic Model of Squash: Strategies and Applications

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  • John Simmons

Abstract

Optimal strategies for squash are presented assuming that the game can be modelled as a Markov chain. Further implications of this model are discussed in relation to handicapping and the correspondence between different scoring systems. The validity of the model is briefly discussed in the light of data.

Suggested Citation

  • John Simmons, 1989. "A Probabilistic Model of Squash: Strategies and Applications," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 95-110, March.
    • Handle: RePEc:bla:jorssc:v:38:y:1989:i:1:p:95-110
    DOI: 10.2307/2347684
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    Cited by:

    1. Gonzalez-Cabrera Ivan & Herrera Diego Dario & González Diego Luis, 2020. "Generalized model for scores in volleyball matches," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(1), pages 41-55, March.
    2. Davy Paindaveine & Yvik Swan, 2009. "A stochastic analysis of some two-person sports," Working Papers ECARES 2009_025, ULB -- Universite Libre de Bruxelles.
    3. Jeryl L. Mumpower, 2011. "Playing Squash Against Ralph Keeney: Should Weaker Players Always Prefer Shorter Games?," Decision Analysis, INFORMS, vol. 8(1), pages 71-77, March.
    4. Galeano, Javier & Gómez, Miguel-Ángel & Rivas, Fernando & Buldú, Javier M., 2022. "Using Markov chains to identify player’s performance in badminton," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).

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