IDEAS home Printed from
   My bibliography  Save this article

Predicting the Maximum Lead from Final Scores in Basketball: A Diffusion Model


  • Schwarz Wolf

    (University of Potsdam, Germany)


We present an analysis of a time-dependent stochastic model of the real-time progress of the difference between the home and the away team's scores in sports contests. The model was originally proposed by Stern (1994) and treats the evolution of the home team lead (or deficit) as a Wiener diffusion process. We derive the distribution, the mean, and the variance, of the maximum home team lead during one match, both unconditionally, and also conditional on the final score. We present estimates of the model's parameters, and apply the model to the joint distribution of the maximum home team lead and the final results of one complete season (2010/2011) of the top German basketball league. The diffusion model predicts the maximum home team lead from the final results fairly accurately which suggests that static result-oriented accounts may profitably be complemented by dynamic accounts which model the real-time events leading up to the final score.

Suggested Citation

  • Schwarz Wolf, 2012. "Predicting the Maximum Lead from Final Scores in Basketball: A Diffusion Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(4), pages 1-15, November.
  • Handle: RePEc:bpj:jqsprt:v:8:y:2012:i:4:n:3

    Download full text from publisher

    File URL:
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

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

    References listed on IDEAS

    1. Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
    2. Jonah Berger & Devin Pope, 2011. "Can Losing Lead to Winning?," Management Science, INFORMS, vol. 57(5), pages 817-827, May.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:8:y:2012:i:4:n:3. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.