IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v12y2016i1p17-30n1.html
   My bibliography  Save this article

An analytical approach for fantasy football draft and lineup management

Author

Listed:
  • Becker Adrian

    (Dynamic Ideas LLC, 465 Waverley Oaks Road, Suite 315, Waltham, MA 02452, USA)

  • Sun Xu Andy

    (Georgia Institute of Technology – Industrial and Systems Engineering, 755 Ferst Drive, Atlanta, GA 30332, USA)

Abstract

In this paper, we consider fantasy football, an increasingly-popular online game based on the actual, on-the-field performances of players in the National Football League. It is estimated by the Fantasy Sports Trade Association that in 2011 there were 35 million people in the US and Canada playing fantasy sports online. About 85 percent of all fantasy sports participants play fantasy football, most of whom have their games set up in major media websites such as Yahoo!, ESPN, MSN, and NFL. Numerous websites specialize in reporting NFL games, providing preseason rankings, fantasy points projections, team and player statistics, and expert draft opinions. However, despite the vast popularity of the game, the intensive analysis by experts, and various online tools that offer prediction for the values of players, to the best of our knowledge, there is no method that provides a comprehensive optimization strategy for the entire Fantasy Football season. We set out to develop such a methodology that predicts team and player performance based on the rich historical data, and builds a mixed-integer optimization model using such predictions for the draft selection as well as weekly line-up management that incorporates the entire objective of winning a fantasy football season. Numerical tests of our model show promising performance.

Suggested Citation

  • Becker Adrian & Sun Xu Andy, 2016. "An analytical approach for fantasy football draft and lineup management," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(1), pages 17-30, March.
    • Handle: RePEc:bpj:jqsprt:v:12:y:2016:i:1:p:17-30:n:1
    DOI: 10.1515/jqas-2013-0009
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jqas-2013-0009
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/jqas-2013-0009?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. Fry Michael J & Lundberg Andrew W & Ohlmann Jeffrey W, 2007. "A Player Selection Heuristic for a Sports League Draft," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(2), pages 1-35, April.
    2. Cade Massey & Richard H. Thaler, 2013. "The Loser's Curse: Decision Making and Market Efficiency in the National Football League Draft," Management Science, INFORMS, vol. 59(7), pages 1479-1495, July.
    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. Vojtěch Kotrba, 2020. "Heuristics in fantasy sports: is it profitable to strategize based on favourite of the match?," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 19(1), pages 195-206, June.
    2. Pantuso Giovanni, 2017. "The Football Team Composition Problem: a Stochastic Programming approach," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(3), pages 113-129, September.
    3. Yurko Ronald & Ventura Samuel & Horowitz Maksim, 2019. "nflWAR: a reproducible method for offensive player evaluation in football," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(3), pages 163-183, September.

    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. Vojtěch Kotrba, 2020. "Heuristics in fantasy sports: is it profitable to strategize based on favourite of the match?," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 19(1), pages 195-206, June.
    2. repec:cup:judgdm:v:17:y:2022:i:4:p:691-719 is not listed on IDEAS
    3. repec:jdm:journl:v:17:y:2022:i:4:p:691-719 is not listed on IDEAS
    4. Sivan Frenkel & Yuval Heller & Roee Teper, 2018. "The Endowment Effect As Blessing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(3), pages 1159-1186, August.
    5. Ian Gregory-Smith & Alex Bryson & Rafael Gomez, 2023. "Discrimination in a Rank Order Contest: Evidence from the NFL Draft," Journal of Economics, Race, and Policy, Springer, vol. 6(3), pages 215-231, September.
    6. Craig, J. Dean & Winchester, Niven, 2021. "Predicting the national football league potential of college quarterbacks," European Journal of Operational Research, Elsevier, vol. 295(2), pages 733-743.
    7. repec:hal:spmain:info:hdl:2441/7fsnj6af7v9ncrf76qn5p5on9e is not listed on IDEAS
    8. Jemuel Chandrakumaran, 2022. "An Experimental Method in Juxtaposing Draft Picks and Active Players," Economic Papers, The Economic Society of Australia, vol. 41(1), pages 68-77, March.
    9. Tobias Berger & Frank Daumann, 2021. "Anchoring bias in the evaluation of basketball players: A closer look at NBA draft decision‐making," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1248-1262, July.
    10. Masaki Fujimoto, 2023. "A Dynamic Analysis of Equal Revenue Sharing and Endogenous Salary Caps in the N-Team Leagues," Journal of Sports Economics, , vol. 24(5), pages 624-638, June.
    11. Evan Polman & Lyn M. Van Swol & Paul R. Hoban, 2020. "Harbingers of foul play: A field study of gain/loss frames and regulatory fit in the NFL," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(3), pages 353-370, May.
    12. Bar-Eli, Michael & Krumer, Alex & Morgulev, Elia, 2020. "Ask not what economics can do for sports - Ask what sports can do for economics," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    13. John A List & Ian Muirex & Devin Pope & Gregory Sun, 2023. "Left-Digit Bias at Lyft," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(6), pages 3186-3237.
    14. Quinn A. W. Keefer, 2019. "Do sunk costs affect expert decision making? Evidence from the within-game usage of NFL running backs," Empirical Economics, Springer, vol. 56(5), pages 1769-1796, May.
    15. Avugos, Simcha & Azar, Ofer H. & Sher, Eran & Gavish, Nadav & Bar-Eli, Michael, 2020. "The Right-Oriented Bias in Soccer Penalty Shootouts," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    16. Philip L. Hersch & Jodi E. Pelkowski, 2016. "Are there too few trades during the NFL draft?," Applied Economics Letters, Taylor & Francis Journals, vol. 23(7), pages 516-519, May.
    17. Dirk E. Black & Marshall D. Vance, 2021. "Do First Impressions Last? The Impact of Initial Assessments and Subsequent Performance on Promotion Decisions," Management Science, INFORMS, vol. 67(7), pages 4556-4576, July.
    18. Michael A. Roach, 2022. "Career concerns and personnel investment in the Major League Baseball player draft," Economic Inquiry, Western Economic Association International, vol. 60(1), pages 413-426, January.
    19. Tony Caporale & Trevor Collier, 2015. "Are We Getting Better or Are They Getting Worse? Draft Position, Strength of Schedule, and Competitive Balance in the National Football League," Journal of Labor Research, Springer, vol. 36(3), pages 291-300, September.
    20. Quinn A. W. Keefer & Thomas J. Kniesner, 2023. "“Injury risk, concussions, race, and pay in the NFL”," Journal of Risk and Uncertainty, Springer, vol. 67(2), pages 107-136, October.
    21. Ulrike Malmendier, 2018. "Behavioral Corporate Finance," NBER Working Papers 25162, National Bureau of Economic Research, Inc.
    22. Jan Schnellenbach & Christian Schubert, 2019. "A note on the behavioral political economy of innovation policy," Journal of Evolutionary Economics, Springer, vol. 29(5), pages 1399-1414, November.
    23. Zaytseva, I. & Stupin, M., 2023. "The key to the "Moneyball" phenomenon: What are the determinants of the level of effort in absence of fi nancial motivation in professional football?," Journal of the New Economic Association, New Economic Association, vol. 60(3), pages 12-26.

    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:bpj:jqsprt:v:12:y:2016:i:1:p:17-30:n:1. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.