IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v325y2023i1d10.1007_s10479-022-04524-7.html
   My bibliography  Save this article

Simulation-based decision making in the NFL using NFLSimulatoR

Author

Listed:
  • Benjamin Williams

    (University of Denver)

  • Will Palmquist

    (University of Denver)

  • Ryan Elmore

    (University of Denver)

Abstract

In this paper, we introduce an R software package for simulating plays and drives using play-by-play data from the National Football League. The simulations are generated by sampling play-by-play data from previous football seasons. The sampling procedure adds statistical rigor to any decisions or inferences arising from examining the simulations. We highlight that the package is particularly useful as a data-driven tool for evaluating potential in-game strategies or rule changes within the league. We demonstrate its utility by evaluating the oft-debated strategy of “going for it” on fourth down and investigating whether or not teams should pass more than the current standard.

Suggested Citation

  • Benjamin Williams & Will Palmquist & Ryan Elmore, 2023. "Simulation-based decision making in the NFL using NFLSimulatoR," Annals of Operations Research, Springer, vol. 325(1), pages 731-742, June.
    • Handle: RePEc:spr:annopr:v:325:y:2023:i:1:d:10.1007_s10479-022-04524-7
    DOI: 10.1007/s10479-022-04524-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-04524-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-022-04524-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kenneth Kovash & Steven D. Levitt, 2009. "Professionals Do Not Play Minimax: Evidence from Major League Baseball and the National Football League," NBER Working Papers 15347, National Bureau of Economic Research, Inc.
    2. David Romer, 2006. "Do Firms Maximize? Evidence from Professional Football," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 340-365, April.
    Full references (including those not matched with items on IDEAS)

    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. Emara, Noha & Owens, David & Smith, John & Wilmer, Lisa, 2017. "Serial correlation in National Football League play calling and its effects on outcomes," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 69(C), pages 125-132.
    2. Jared Quenzel & Paul Shea, 2016. "Predicting the Winner of Tied National Football League Games," Journal of Sports Economics, , vol. 17(7), pages 661-671, October.
    3. Paserman, M. Daniele, 2023. "Gender Differences in Performance in Competitive Environments? Evidence from Professional Tennis Players," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 590-609.
    4. Michael William Gmeiner, 2019. "History-Dependent Mixed Strategies: Evidence From Major League Baseball," Journal of Sports Economics, , vol. 20(3), pages 371-398, April.
    5. Lefgren, Lars J. & Platt, Brennan & Price, Joseph & Higbee, Samuel, 2019. "Outcome based accountability: Theory and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 160(C), pages 121-137.
    6. Urschel John D & Zhuang Jun, 2011. "Are NFL Coaches Risk and Loss Averse? Evidence from Their Use of Kickoff Strategies," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-17, July.
    7. Lopez Michael J., 2020. "Bigger data, better questions, and a return to fourth down behavior: an introduction to a special issue on tracking datain the National football League," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(2), pages 73-79, June.
    8. Fort, Rodney & Maxcy, Joel & Diehl, Mark, 2016. "Uncertainty by regulation: Rottenberg׳s invariance principle," Research in Economics, Elsevier, vol. 70(3), pages 454-467.
    9. Heifetz, Aviad & Heller, Ruth & Ostreiher, Roni, 2021. "Do Arabian babblers play mixed strategies in a “volunteer’s dilemma”?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 91(C).
    10. repec:hal:spmain:info:hdl:2441/7fsnj6af7v9ncrf76qn5p5on9e is not listed on IDEAS
    11. Michele Fioretti, 2022. "Caring or Pretending to Care? Social Impact, Firms' Objectives, and Welfare (former title: Social Responsibility and Firm's Objectives)," SciencePo Working papers hal-03393065, HAL.
    12. Romain Gauriot & Lionel Page & John Wooders, 2016. "Nash at Wimbledon: Evidence from Half a Million Serves," QuBE Working Papers 046, QUT Business School.
    13. Adams, Christopher P., 2007. "Estimating demand from eBay prices," International Journal of Industrial Organization, Elsevier, vol. 25(6), pages 1213-1232, December.
    14. Kotchen, Matthew J. & Potoski, Matthew, 2014. "Conflicts of interest distort public evaluations: Evidence from NCAA football coaches," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 51-63.
    15. Ozbeklik, Serkan & Smith, Janet Kiholm, 2017. "Risk taking in competition: Evidence from match play golf tournaments," Journal of Corporate Finance, Elsevier, vol. 44(C), pages 506-523.
    16. Goldman, Matt & Rao, Justin M., 2017. "Optimal stopping in the NBA: Sequential search and the shot clock," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 107-124.
    17. Pedro Garcia-del-Barrio & Stefan Szymanski, 2006. "Goal! Profit maximization and win maximization in football leagues," Working Papers 0621, International Association of Sports Economists;North American Association of Sports Economists.
    18. Michael A. Roach & Mark F. Owens, 2024. "Updating Beliefs Based on Observed Performance: Evidence From NFL Head Coaches," Journal of Sports Economics, , vol. 25(3), pages 369-387, April.
    19. V. Bhaskar, 2009. "Rational Adversaries? Evidence from Randomised Trials in One Day Cricket," Economic Journal, Royal Economic Society, vol. 119(534), pages 1-23, January.
    20. Romain Gauriot & Lionel Page & John Wooders, 2016. "Nash at Wimbledon: Evidence from Half a Million Serves," QuBE Working Papers 046, QUT Business School.
    21. Sean Duffy & J. J. Naddeo & David Owens & John Smith, 2024. "Cognitive Load and Mixed Strategies: On Brains and Minimax," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-34, September.

    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:spr:annopr:v:325:y:2023:i:1:d:10.1007_s10479-022-04524-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.