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Baseball, Optimization, and the World Wide Web


  • 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)


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

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    References listed on IDEAS

    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.
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