IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this article

Estimating Production Efficiency in Men’s NCAA College Basketball: A Bayesian Approach

Listed author(s):
  • Michael S. Rimler

    (Xavier University)

  • Seongho Song

    (University of Cincinnati)

  • David T. Yi

    (Xavier University)

Registered author(s):

    Using Bayesian analysis with Markov Chain Monte Carlo (MCMC) estimation, we generate estimates of technical efficiency for each game played by an Atlantic 10 Conference men’s basketball team during the 2005-2006 season. The flexibility of MCMC, and its ability to provide an objective measure for assessing model fit, makes it preferable to maximum likelihood (ML) estimation of stochastic production frontiers. Within the context of men’s basketball, this article addresses the question of whether technical efficiency necessarily leads to success relative to one’s competitors. Results indicate that (a) technical efficiency does not vary significantly, either across or within teams, implying that teams in the A-10 play at very close and high levels of efficiency and (b) technical efficiency does not correlate strongly with productivity, suggesting that the fundamental quality of one’s resources are more important than an efficient use of those resources. In addition, parameter estimates suggest that a single turnover or offensive rebound could mean the difference between winning and losing.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Article provided by in its journal Journal of Sports Economics.

    Volume (Year): 11 (2010)
    Issue (Month): 3 (June)
    Pages: 287-315

    in new window

    Handle: RePEc:sae:jospec:v:11:y:2010:i:3:p:287-315
    Contact details of provider:

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:sae:jospec:v:11:y:2010:i:3:p:287-315. 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: (SAGE Publications)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.