IDEAS home Printed from https://ideas.repec.org/a/wly/soecon/v76y2010i3p791-810.html
   My bibliography  Save this article

Pass or Run: An Empirical Test of the Matching Pennies Game Using Data from the National Football League

Author

Listed:
  • Joseph P. McGarrity
  • Brian Linnen

Abstract

This article examines play calling in the National Football League (NFL). It finds that a mixed strategy equilibrium game explains NFL play calling better than standard optimization techniques. When a quarterback is injured and replaced with a less capable backup, standard optimization theory suggests that the offense will run more often, passing less. Our game theoretic model predicts that the offense will not change its play calling because the defense will play against the run more often. Using every first half play from the 11 teams that had a starting quarterback miss action because of injury in the 2006 season, we find that the injury did not alter the likelihood that the offense would pass. We also find that coaches randomly mix passing and running plays, as the mixed strategy games predict.

Suggested Citation

  • Joseph P. McGarrity & Brian Linnen, 2010. "Pass or Run: An Empirical Test of the Matching Pennies Game Using Data from the National Football League," Southern Economic Journal, John Wiley & Sons, vol. 76(3), pages 791-810, January.
    • Handle: RePEc:wly:soecon:v:76:y:2010:i:3:p:791-810
    DOI: 10.4284/sej.2010.76.3.791
    as

    Download full text from publisher

    File URL: https://doi.org/10.4284/sej.2010.76.3.791
    Download Restriction: no
    File URL: https://libkey.io/10.4284/sej.2010.76.3.791?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
    ---><---

    References listed on IDEAS

    as
    1. Daniel Sutter & Stephen Winkler, 2003. "Ncaa Scholarship Limits and Competitive Balance in College Football," Journal of Sports Economics, , vol. 4(1), pages 3-18, February.
    2. Goff, Brian L & Shughart, William F, II & Tollison, Robert D, 1997. "Batter Up! Moral Hazard and the Effects of the Designated Hitter Rule on Hit Batsmen," Economic Inquiry, Western Economic Association International, vol. 35(3), pages 555-561, July.
    3. William Greene, 2004. "Fixed Effects and Bias Due to the Incidental Parameters Problem in the Tobit Model," Econometric Reviews, Taylor & Francis Journals, vol. 23(2), pages 125-147.
    4. John Charles Bradbury & Douglas J. Drinen, 2007. "Crime And Punishment In Major League Baseball: The Case Of The Designated Hitter And Hit Batters," Economic Inquiry, Western Economic Association International, vol. 45(1), pages 131-144, January.
    5. Coupé, Tom, 2005. "Bias in Conditional and Unconditional Fixed Effects Logit Estimation: A Correction," Political Analysis, Cambridge University Press, vol. 13(3), pages 292-295, July.
    6. William Greene, 2004. "The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 98-119, June.
    7. Brian L. Goff & Robert E. McCormick & Robert D. Tollison, 2002. "Racial Integration as an Innovation: Empirical Evidence from Sports Leagues," American Economic Review, American Economic Association, vol. 92(1), pages 16-26, March.
    8. Mark Walker & John Wooders, 2001. "Minimax Play at Wimbledon," American Economic Review, American Economic Association, vol. 91(5), pages 1521-1538, December.
    9. Jac C. Heckelman & Andrew J. Yates, 2003. "And a Hockey Game Broke Out: Crime and Punishment in the NHL," Economic Inquiry, Western Economic Association International, vol. 41(4), pages 705-712, October.
    10. McCormick, Robert E & Tollison, Robert D, 1984. "Crime on the Court," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 223-235, April.
    11. P.-A. Chiappori, 2002. "Testing Mixed-Strategy Equilibria When Players Are Heterogeneous: The Case of Penalty Kicks in Soccer," American Economic Review, American Economic Association, vol. 92(4), pages 1138-1151, September.
    12. Ignacio Palacios-Huerta, 2001. "Professionals Play Minimax," Working Papers 2001-17, Brown University, Department of Economics.
    13. Katz, Ethan, 2001. "Bias in Conditional and Unconditional Fixed Effects Logit Estimation," Political Analysis, Cambridge University Press, vol. 9(4), pages 379-384, January.
    14. Klaassen, Franc J.G.M. & Magnus, Jan R., 2009. "The efficiency of top agents: An analysis through service strategy in tennis," Journal of Econometrics, Elsevier, vol. 148(1), pages 72-85, January.
    15. Germán Coloma, 2007. "Penalty Kicks in Soccer," Journal of Sports Economics, , vol. 8(5), pages 530-545, October.
    16. Marc Poitras, 2006. "Do New Major League Ballparks Pay for Themselves?," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2275-2300, September.
    17. Ignacio Palacios-Huerta, 2003. "Professionals Play Minimax," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 395-415.
    18. Shih-Hsun Hsu & Chen-Ying Huang & Cheng-Tao Tang, 2007. "Minimax Play at Wimbledon: Comment," American Economic Review, American Economic Association, vol. 97(1), pages 517-523, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Charles A. Holt & Ricky Sahu & Angela M. Smith, 2022. "An experimental analysis of risk effects in attacker‐defender games," Southern Economic Journal, John Wiley & Sons, vol. 89(1), pages 185-215, July.

    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. Luigi Buzzacchi & Stefano Pedrini, 2014. "Does player specialization predict player actions? Evidence from penalty kicks at FIFA World Cup and UEFA Euro Cup," Applied Economics, Taylor & Francis Journals, vol. 46(10), pages 1067-1080, April.
    3. Axel Anderson & Jeremy Rosen & John Rust & Kin-Ping Wong, 2021. "Disequilibrium Play in Tennis," Working Papers gueconwpa~21-21-07, Georgetown University, Department of Economics.
    4. Jim Downey & Joseph McGarrity, 2015. "Pick off Throws, Stolen Bases, and Southpaws: A Comparative Static Analysis of a Mixed Strategy Game," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 43(3), pages 319-335, September.
    5. Thomas Dohmen & Hendrik Sonnabend, 2018. "Further Field Evidence for Minimax Play," Journal of Sports Economics, , vol. 19(3), pages 371-388, April.
    6. Duffy, Sean & Naddeo, JJ & Owens, David & Smith, John, 2016. "Cognitive load and mixed strategies: On brains and minimax," MPRA Paper 71878, University Library of Munich, Germany.
    7. Leonidas Spiliopoulos, 2018. "Randomization and serial dependence in professional tennis matches: Do strategic considerations, player rankings and match characteristics matter?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(5), pages 413-427, September.
    8. repec:cup:judgdm:v:13:y:2018:i:5:p:413-427 is not listed on IDEAS
    9. Emara, Noha & Owens, David & Smith, John & Wilmer, Lisa, 2014. "Minimax on the gridiron: Serial correlation and its effects on outcomes in the National Football League," MPRA Paper 58907, University Library of Munich, Germany.
    10. Van Essen, Matt & Wooders, John, 2015. "Blind stealing: Experience and expertise in a mixed-strategy poker experiment," Games and Economic Behavior, Elsevier, vol. 91(C), pages 186-206.
    11. Steven D. Levitt & John A. List & David H. Reiley, 2010. "What Happens in the Field Stays in the Field: Exploring Whether Professionals Play Minimax in Laboratory Experiments," Econometrica, Econometric Society, vol. 78(4), pages 1413-1434, July.
    12. 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.
    13. Jin-Hyuk Kim, 2013. "Does competition affect evolutionary dynamics? Evidence from a collegiate university," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 781-785, May.
    14. Spenkuch, Jörg, 2014. "Backward Induction in the Wild: Evidence from the U.S. Senate," MPRA Paper 58766, University Library of Munich, Germany.
    15. Okano, Yoshitaka, 2013. "Minimax play by teams," Games and Economic Behavior, Elsevier, vol. 77(1), pages 168-180.
    16. Giancarlo Moschini, 2010. "Incentives And Outcomes In A Strategic Setting: The 3‐Points‐For‐A‐Win System In Soccer," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 65-79, January.
    17. Brian Goff & Stephen L. Locke, 2019. "Revisiting Romer: Digging Deeper Into Influences on NFL Managerial Decisions," Journal of Sports Economics, , vol. 20(5), pages 671-689, June.
    18. Alexander W. Salter, 2017. "Strategic Offsetting Behavior in the NBA," Journal of Sports Economics, , vol. 18(2), pages 126-139, February.
    19. Jim Downey & Joseph McGarrity, 2019. "Pressure and the ability to randomize decision-making: The case of the pickoff play in Major League Baseball," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(3), pages 261-274, September.
    20. John Wooders, 2010. "Does Experience Teach? Professionals and Minimax Play in the Lab," Econometrica, Econometric Society, vol. 78(3), pages 1143-1154, May.
    21. Jung S You, 2021. "Random Actions in Experimental Zero-Sum Games," Journal of Economics and Behavioral Studies, AMH International, vol. 13(1), pages 69-81.

    More about this item

    Statistics

    Access and download statistics

    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:wly:soecon:v:76:y:2010:i:3:p:791-810. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)2325-8012 .

    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.