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Realignment in the National Football League: Did they do it right?

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  • John E. Mitchell

Abstract

The National Football League (NFL) in the United States expanded to 32 teams in 2002 with the addition of a team in Houston. At that point, the league was realigned into eight divisions, each containing four teams. We describe a branch‐and‐cut algorithm for minimizing the sum of intradivisional travel distances. We consider first the case where any team can be assigned to any division. We also consider imposing restrictions, such as aligning the AFC (American Football Conference) and the NFC (National Football Conference) separately or maintaining traditional rivalries. We show that the alignment chosen by the NFL does not minimize the sum of intradivisional travel distances, but that it is close to optimal for an alignment that aligns the NFC and AFC separately and imposes some additional restrictions. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 683–701, 2003.

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  • 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.
    • Handle: RePEc:wly:navres:v:50:y:2003:i:7:p:683-701
    DOI: 10.1002/nav.10084
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    References listed on IDEAS

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    1. James C. Bean & John R. Birge, 1980. "Reducing Travelling Costs and Player Fatigue in the National Basketball Association," Interfaces, INFORMS, vol. 10(3), pages 98-102, June.
    2. FERREIRA, C. E. & MARTIN, A. & de SOUZA, C. C. & WEISMANTEL, R., 1996. "Formulations and valid inequalities for the node capacitated graph partitioning problem," LIDAM Reprints CORE 1236, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. FERREIRA, Carlos E. & MARTIN, Alexander & de SOUZA, Cid C. & WEISMANTEL, Robert, 1998. "The node capacitated graph partitioning problem: A computational study," LIDAM Reprints CORE 1335, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Saltzman, Robert M. & Bradford, Richard M., 1996. "Optimal realignments of the teams in the National Football League," European Journal of Operational Research, Elsevier, vol. 93(3), pages 469-475, September.
    5. 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.
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    Cited by:

    1. Diego Recalde & Ramiro Torres & Polo Vaca, 2020. "An exact approach for the multi-constraint graph partitioning problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 289-308, October.
    2. Fuda Ma & Jin-Kao Hao, 2017. "A multiple search operator heuristic for the max-k-cut problem," Annals of Operations Research, Springer, vol. 248(1), pages 365-403, January.
    3. Vilmar Jefté Rodrigues de Sousa & Miguel F. Anjos & Sébastien Le Digabel, 2019. "Improving the linear relaxation of maximum k-cut with semidefinite-based constraints," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 7(2), pages 123-151, June.
    4. Li, Miao & Davari, Morteza & Goossens, Dries, 2023. "Multi-league sports scheduling with different leagues sizes," European Journal of Operational Research, Elsevier, vol. 307(1), pages 313-327.
    5. Bissan Ghaddar & Miguel Anjos & Frauke Liers, 2011. "A branch-and-cut algorithm based on semidefinite programming for the minimum k-partition problem," Annals of Operations Research, Springer, vol. 188(1), pages 155-174, August.
    6. Diego Recalde & Daniel Severín & Ramiro Torres & Polo Vaca, 2018. "An exact approach for the balanced k-way partitioning problem with weight constraints and its application to sports team realignment," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 916-936, October.
    7. Vilmar Jefté Rodrigues de Sousa & Miguel F. Anjos & Sébastien Le Digabel, 2018. "Computational study of valid inequalities for the maximum k-cut problem," Annals of Operations Research, Springer, vol. 265(1), pages 5-27, June.

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