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Ranking Sports Teams: A Customizable Quadratic Assignment Approach

Author

Listed:
  • C. Richard Cassady

    (Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, Arkansas 72701)

  • Lisa M. Maillart

    (Department of Operations, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106)

  • Sinan Salman

    (Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, Arkansas 72701)

Abstract

Ranking sports teams in the absence of full round-robin tournaments is big business, especially for NCAA Division I-A college football. The Bowl Championship Series awards millions of dollars each year to the conferences whose teams are awarded bids. We formulated the sports-team-ranking problem as a customizable quadratic-assignment problem. Decision makers can tailor our model to suit their personal definitions of the degree of victory for each game played and the relative distance between ranking positions. We developed a parameter-section procedure for determining these customized values and executed it using the 2004 college football season. Because the problem size is so large, we developed a heuristic solution procedure based on a genetic algorithm and local search techniques. This heuristic performs well on a special problem instance in which we can easily identify the optimal ranking. To examine the behavior of our approach, we implemented the heuristic for the 1999 through 2004 college football seasons. We concluded that our approach works best when the margin of victory of individual games is not considered, the location of games is considered, and the date of games is considered. Finally, we evaluated how our approach would have weighed in on several recent controversies in NCAA Division I-A college football and found that our approach generally agrees with traditional schools of thought regarding these controversies.

Suggested Citation

  • C. Richard Cassady & Lisa M. Maillart & Sinan Salman, 2005. "Ranking Sports Teams: A Customizable Quadratic Assignment Approach," Interfaces, INFORMS, vol. 35(6), pages 497-510, December.
  • Handle: RePEc:inm:orinte:v:35:y:2005:i:6:p:497-510
    DOI: 10.1287/inte.1050.0171
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    References listed on IDEAS

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    1. Rick L. Wilson, 1995. "Ranking College Football Teams: A Neural Network Approach," Interfaces, INFORMS, vol. 25(4), pages 44-59, August.
    2. Iqbal Ali & Wade D. Cook & Moshe Kress, 1986. "On the Minimum Violations Ranking of a Tournament," Management Science, INFORMS, vol. 32(6), pages 660-672, June.
    3. Stephen T. Goddard, 1983. "Ranking in Tournaments and Group Decisionmaking," Management Science, INFORMS, vol. 29(12), pages 1384-1392, December.
    4. Joseph Martinich, 2002. "College Football Rankings: Do the Computers Know Best?," Interfaces, INFORMS, vol. 32(5), pages 85-94, October.
    5. Michael Stob, 1985. "Note---Rankings from Round-Robin Tournaments," Management Science, INFORMS, vol. 31(9), pages 1191-1195, September.
    6. Zvi Drezner, 2003. "A New Genetic Algorithm for the Quadratic Assignment Problem," INFORMS Journal on Computing, INFORMS, vol. 15(3), pages 320-330, August.
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    Cited by:

    1. Brian McClure & Richard Cassady & Chase Rainwater & Justin R. Chimka, 2012. "Optimizing the Sunday Singles Lineup for a Ryder Cup Captain," Interfaces, INFORMS, vol. 42(2), pages 180-190, April.
    2. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
    3. G Kendall, 2008. "Scheduling English football fixtures over holiday periods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 743-755, June.

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