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Optimizing the allocation of funds of an NFL team under the salary cap

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  • Mulholland, Jason
  • Jensen, Shane T.

Abstract

Every NFL team faces the complex decision of having to choose how to allocate salaries to each position while being limited by the salary cap. This paper uses regression strategies to identify which positions are worthy of greater investment, under the assumption that players are paid in an efficient market. Using a combination of univariate regression models, we identify that it is worth investing in elite players at the quarterback, guard, defensive line, and linebacker positions. In addition, through a separate set of regression models we also consider the possibility that markets are not actually efficient. We determine that the optimal way to take advantage of inefficiency is through the draft, in order to find players who can provide significant win contributions early in their careers while they are being paid on relatively low rookie contracts.

Suggested Citation

  • Mulholland, Jason & Jensen, Shane T., 2019. "Optimizing the allocation of funds of an NFL team under the salary cap," International Journal of Forecasting, Elsevier, vol. 35(2), pages 767-775.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:2:p:767-775
    DOI: 10.1016/j.ijforecast.2018.09.004
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    References listed on IDEAS

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    1. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part I: General Sports Applications," Interfaces, INFORMS, vol. 42(2), pages 105-108, April.
    2. Michael A. Leeds & Sandra Kowalewski, 2001. "Winner Take All in the NFL," Journal of Sports Economics, , vol. 2(3), pages 244-256, August.
    3. Michael J. Fry & Jeffrey W. Ohlmann, 2012. "Introduction to the Special Issue on Analytics in Sports, Part II: Sports Scheduling Applications," Interfaces, INFORMS, vol. 42(3), pages 229-231, June.
    4. Borghesi, Richard, 2008. "Allocation of scarce resources: Insight from the NFL salary cap," Journal of Economics and Business, Elsevier, vol. 60(6), pages 536-550.
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    Cited by:

    1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    2. Sabin R. Paul, 2021. "Estimating player value in American football using plus–minus models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(4), pages 313-364, December.

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