IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v32y2002i2p12-22.html
   My bibliography  Save this article

Baseball, Optimization, and the World Wide Web

Author

Listed:
  • Ilan Adler

    (Department of Industrial Engineering and Operations Research, 4135 Etcheverry Hall, University of California, Berkeley, California 94720)

  • Alan L. Erera

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205)

  • Dorit S. Hochbaum

    (Department of Industrial Engineering and Operations Research, 4135 Etcheverry Hall, University of California, Berkeley, California 94720)

  • Eli V. Olinick

    (Department of Computer Science and Engineering, Southern Methodist University, P.O. Box 750122, Dallas, Texas 75275-0122)

Abstract

The competition for baseball play-off spots—the fabled pennant race—is one of the most closely watched American sports traditions. While play-off race statistics, such as games back and magic number, are informative, they are overly conservative and do not account for the remaining schedule of games. Using optimization techniques, one can model schedule effects explicitly and determine precisely when a team has secured a play-off spot or has been eliminated from contention. The RIOT Baseball Play-off Races Web site developed at the University of California, Berkeley, provides automatic updates of new, optimization-based play-off race statistics each day of the major league baseball season. In developing the site, we found that we could determine the first-place elimination status of all teams in a division using a single linear-programming formulation, since a minimum win threshold for teams finishing in first place applies to all teams in a division. We identified a similar (but weaker) result for the problem of play-off elimination with wildcard teams.

Suggested Citation

  • Ilan Adler & Alan L. Erera & Dorit S. Hochbaum & Eli V. Olinick, 2002. "Baseball, Optimization, and the World Wide Web," Interfaces, INFORMS, vol. 32(2), pages 12-22, April.
  • Handle: RePEc:inm:orinte:v:32:y:2002:i:2:p:12-22
    DOI: 10.1287/inte.32.2.12.67
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.32.2.12.67
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.32.2.12.67?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
    ---><---

    References listed on IDEAS

    as
    1. S. Thomas McCormick, 1999. "Fast Algorithms for Parametric Scheduling Come From Extensions to Parametric Maximum Flow," Operations Research, INFORMS, vol. 47(5), pages 744-756, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Russell, Tyrel & van Beek, Peter, 2012. "A hybrid constraint programming and enumeration approach for solving NHL playoff qualification and elimination problems," European Journal of Operational Research, Elsevier, vol. 218(3), pages 819-828.
    2. Raack Christian & Raymond Annie & Schlechte Thomas & Werner Axel, 2014. "Standings in sports competitions using integer programming," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 131-137, June.
    3. John E. Mitchell, 2003. "Realignment in the National Football League: Did they do it right?," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(7), pages 683-701, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sedeno-Noda, A. & Alcaide, D. & Gonzalez-Martin, C., 2006. "Network flow approaches to pre-emptive open-shop scheduling problems with time-windows," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1501-1518, November.
    2. Stephan Helfrich & Arne Herzel & Stefan Ruzika & Clemens Thielen, 2022. "An approximation algorithm for a general class of multi-parametric optimization problems," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1459-1494, October.
    3. Akiyoshi Shioura & Natalia V. Shakhlevich & Vitaly A. Strusevich, 2017. "Machine Speed Scaling by Adapting Methods for Convex Optimization with Submodular Constraints," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 724-736, November.
    4. Akiyoshi Shioura & Natalia V. Shakhlevich & Vitaly A. Strusevich, 2020. "Scheduling problems with controllable processing times and a common deadline to minimize maximum compression cost," Journal of Global Optimization, Springer, vol. 76(3), pages 471-490, March.
    5. Klamroth, Kathrin & Wiecek, Margaret M., 2001. "A time-dependent multiple criteria single-machine scheduling problem," European Journal of Operational Research, Elsevier, vol. 135(1), pages 17-26, November.
    6. Maria Scutellà, 2007. "A note on the parametric maximum flow problem and some related reoptimization issues," Annals of Operations Research, Springer, vol. 150(1), pages 231-244, March.
    7. Sedeño-Noda, A. & de Pablo, D. Alcaide López & González-Martín, C., 2009. "A network flow-based method to solve performance cost and makespan open-shop scheduling problems with time-windows," European Journal of Operational Research, Elsevier, vol. 196(1), pages 140-154, July.
    8. Akiyoshi Shioura & Natalia V. Shakhlevich & Vitaly A. Strusevich, 2016. "Application of Submodular Optimization to Single Machine Scheduling with Controllable Processing Times Subject to Release Dates and Deadlines," INFORMS Journal on Computing, INFORMS, vol. 28(1), pages 148-161, February.
    9. Shioura, Akiyoshi & Shakhlevich, Natalia V. & Strusevich, Vitaly A., 2018. "Preemptive models of scheduling with controllable processing times and of scheduling with imprecise computation: A review of solution approaches," European Journal of Operational Research, Elsevier, vol. 266(3), pages 795-818.
    10. Russell, Tyrel & van Beek, Peter, 2012. "A hybrid constraint programming and enumeration approach for solving NHL playoff qualification and elimination problems," European Journal of Operational Research, Elsevier, vol. 218(3), pages 819-828.
    11. Nir Halman & Mikhail Y. Kovalyov & Alain Quilliot, 2023. "Max–max, max–min, min–max and min–min knapsack problems with a parametric constraint," 4OR, Springer, vol. 21(2), pages 235-246, June.
    12. Cristina Bazgan & Arne Herzel & Stefan Ruzika & Clemens Thielen & Daniel Vanderpooten, 2022. "An approximation algorithm for a general class of parametric optimization problems," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1328-1358, July.

    More about this item

    Keywords

    Recreation and sports;

    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:inm:orinte:v:32:y:2002:i:2:p:12-22. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.