IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v18y2022i2p127-145n5.html
   My bibliography  Save this article

A Markov process approach to untangling intention versus execution in tennis

Author

Listed:
  • Chan Timothy C. Y.
  • Fernandes Craig

    (Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, ON M5S 3G8, Canada)

  • Fearing Douglas S.
  • Kovalchik Stephanie

    (Zelus Analytics, Austin, TX, USA)

Abstract

Value functions are used in sports to determine the optimal action players should employ. However, most literature implicitly assumes that players can perform the prescribed action with known and fixed probability of success. The effect of varying this probability or, equivalently, “execution error” in implementing an action (e.g., hitting a tennis ball to a specific location on the court) on the design of optimal strategies, has received limited attention. In this paper, we develop a novel modeling framework based on Markov reward processes and Markov decision processes to investigate how execution error impacts a player’s value function and strategy in tennis. We power our models with hundreds of millions of simulated tennis shots with 3D ball and 2D player tracking data. We find that optimal shot selection strategies in tennis become more conservative as execution error grows, and that having perfect execution with the empirical shot selection strategy is roughly equivalent to choosing one or two optimal shots with average execution error. We find that execution error on backhand shots is more costly than on forehand shots, and that optimal shot selection on a serve return is more valuable than on any other shot, over all values of execution error.

Suggested Citation

  • Chan Timothy C. Y. & Fernandes Craig & Fearing Douglas S. & Kovalchik Stephanie, 2022. "A Markov process approach to untangling intention versus execution in tennis," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 18(2), pages 127-145, June.
  • Handle: RePEc:bpj:jqsprt:v:18:y:2022:i:2:p:127-145:n:5
    DOI: 10.1515/jqas-2021-0077
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jqas-2021-0077
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/jqas-2021-0077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:18:y:2022:i:2:p:127-145:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.