IDEAS home Printed from https://ideas.repec.org/a/taf/rpanxx/v25y2025i2p175-189.html
   My bibliography  Save this article

An expected shot outcome model for points in elite Gaelic football

Author

Listed:
  • Kevin McDaid
  • Kevin McGuigan
  • Jack McDonnell
  • Kieran Collins

Abstract

This study develops a logistic regression model to predict the likelihood of scoring a point in Gaelic football based on shot characteristics. A total of 3537 shots from 67 elite inter-county games in 2019 are analysed. The findings indicate that shot distance, pressure, type (open play/dead ball), side and team level are significant predictors in the model with shots from open play significantly less likely to result in scores than shots from dead ball situations. Pressure is found to be a key to the model with the model indicating that taking a shot under high pressure as compared to low pressure is similar to taking the shot from approximately 9 m further away. Also, interaction effects between shot type and distance, type and angle, and side and method are found to be significant with the outcome that shots from the left side of the field with the right foot are most likely to be successful. The variation in the difference between expected and actual scores for games is found to be similar across team levels.

Suggested Citation

  • Kevin McDaid & Kevin McGuigan & Jack McDonnell & Kieran Collins, 2025. "An expected shot outcome model for points in elite Gaelic football," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 25(2), pages 175-189, March.
  • Handle: RePEc:taf:rpanxx:v:25:y:2025:i:2:p:175-189
    DOI: 10.1080/24748668.2024.2396222
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24748668.2024.2396222
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/24748668.2024.2396222?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.

    More about this item

    Statistics

    Access and download statistics

    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:taf:rpanxx:v:25:y:2025:i:2:p:175-189. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RPAN20 .

    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.