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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
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Cited by:

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    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.

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