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General

Play Call Strategies and Modeling for Target Outcomes in Football

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Pages 66-75 | Received 20 Jan 2023, Accepted 31 May 2023, Published online: 12 Jul 2023

References

  • Allen, K. (2021), “Bridging the Paradox: Using Markov Chains to Supplement National Football League Play-Calling Strategy,” PhD thesis, Northcentral University.
  • Aubet, F.-X., and Ehrlich, E. (2022), “The Science behind NFL Next Gen Stats’ New Passing Metric,” available at https://www.amazon.science/blog/the-science-behind-nfl-next-gen-stats-new-passing-metric.
  • Beaudoin, D., and Swartz, T. B. (2010), “Strategies for Pulling the Goalie in Hockey,” The American Statistician, 64, 197–204. DOI: 10.1198/tast.2010.09147.
  • Biro, P., and Walker, S. G. (2022), “A Reinforcement Learning based Approach to Play Calling in Football,” Journal of Quantitative Analysis in Sports, 18, 97–112. DOI: 10.1515/jqas-2021-0029.
  • Biro, P., and Walker, S. G. (2023), “Parametric Modeling and Analysis of NFL Run Plays,” Journal of Sports Analytics (to appear).
  • Bouzarth, E., Grannan, B., Harris, J., Hartley, A., Hutson, K., and Morton, E. (2021), “Swing Shift: A Mathematical Approach to Defensive Positioning in Baseball,” Journal of Quantitative Analysis in Sports, 17, 47–55. DOI: 10.1515/jqas-2020-0027.
  • Bowen, M. (2014), “NFL 101: Breaking Down the Basics of the Route Tree,” available at https://bleacherreport.com/articles/2016841-nfl-101-breaking-down-the-basics-of-the-route-tree.
  • Bradley, J. (2018), “Mixing Matching and Sabermetrics: Combining Advanced Analytics and the Generalized Matching Lawin NFL Football Play-Calling,” PhD thesis, Western Michigan University.
  • Brownstein, N. C., Louis, T. A., O’Hagan, A., and Pendergast, J. (2019), “The Role of Expert Judgment in Statistical Inference and Evidence-based Decision-Making,” The American Statistician, 73, 56–68. DOI: 10.1080/00031305.2018.1529623.
  • Burke, B. (2010), “Expected Points (EP) and Expected Points Added (EPA) Explained,” available at https://web.archive.org/web/20210310003124/http://archive.advancedfootballanalytics.com/2010/01/expected-points-ep-and-expected-points.html.
  • Burke, B. (2016), “NYT 4th Down Bot,” available at https://www.nytimes.com/interactive/projects/4thdownbot/index.html.
  • Carroll, B. N., Palmer, P., and Thorn, J. (1988), The Hidden Game of Football, New York, NY: Warner Books.
  • Carvalho, C. M., Polson, N. G. and Scott, J. G. (2009), “Handling Sparsity via the Horseshoe,” in Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, Vol. 5 of Proceedings of Machine Learning Research, eds. D. van Dyk and M. Welling, pp. 73–80, PMLR, Hilton Clearwater Beach Resort, Clearwater Beach, Florida USA.
  • Carvalho, C. M., Polson, N. G. and Scott, J. G. (2010), “The Horseshoe Estimator for Sparse Signals,” Biometrika, 97, 465–480.
  • Ehrlich, E., Callot, L., and Aubet, F.-X. (2021), “Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-Tailed Time Series,” RobustML Workshop - ICLR 2021.
  • Feller, W. (1971), An Introduction to Probability Theory and Its Applications, Volume II, New Delhi: Wiley.
  • Fox, J. T. (2007), “Semiparametric Estimation of Multinomial Discrete-Choice Models Using a Subset of Choices,” RAND Journal of Economics, 38, 1002–1019. DOI: 10.1111/j.0741-6261.2007.00123.x.
  • Geman, S., and Geman, D. (1984), “Stochastic relaxation, Gibbs Distributions, and the Bayesian Restoration of Images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6, 721–741. DOI: 10.1109/tpami.1984.4767596.
  • Gibbs, C., Elmore, R., and Fosdick, B. (2021), “The Causal Effect of a Timeout at Stopping an Opposing Run in the NBA,” arXiv.org.
  • Goldner, K. (2017), “Situational Success: Evaluating Decision-Making in Football,” in Handbook of Statistical Methods and Analyses in Sports, eds. J. Albert, M. E. Glickman, T. B. Swartz, and R. H. Koning, pp. 199–214, New York: Chapman and Hall/CRC.
  • Haley, C. (2021), “Five Ways to Define Presbyterian’s Wacky Season,” available at https://theanalyst.com/na/2021/10/five-ways-to-define-presbyterians-wacky-season/.
  • Hastings, W. K. (1970), “Monte Carlo Sampling Methods using Markov Chains and their Applications,” Biometrika, 57, 97–109. DOI: 10.1093/biomet/57.1.97.
  • Horowitz, J. L., Bolduc, D., Divakar, S., Geweke, J., Gönül, F., Hajivassiliou, V., Koppelman, F. S., Keane, M., Matzkin, R., Rossi, P., and Ruud, P. (1994), “Advances in Random Utility Models Report of the Workshop on Advances in Random Utility Models Duke Invitational Symposium on Choice Modeling Behavior,” Marketing Letters, 5, 311–322. DOI: 10.1007/BF00999207.
  • Krasker, W. (2004), “Description of the Dynamic Programming Model,” available at http://www.footballcommentary.com/dynamicprogramming.htm.
  • Lopez, M. J. (2020), “Bigger Data, Better Questions, and a Return to Fourth Down Behavior: An Introduction to a Special Issue on Tracking Data in the National Football League,” Journal of Quantitative Analysis in Sports, 16, 73–79. DOI: 10.1515/jqas-2020-0057.
  • McFadden, D. (1973), “Conditional Logit Analysis of Qualitative Choice Behaviour,” in Frontiers in Econometrics, ed. P. Zarembka, New York: Academic Press, pp. 105–142.
  • McFadden, D. (1986), “The Choice Theory Approach to Market Research,” Marketing Science, 5, 275–297.
  • Miller, S. (2022), “M.L.B. Bans the Shift and Adds a Pitch Clock for 2023,” available at https://www.nytimes.com/2022/09/09/sports/baseball/mlb-bans-shift.html.
  • Patek, S. D., and Bertsekas, D. P. (1998), Play Selection in American Football: A Case Study in Neuro-Dynamic Programming, Boston, MA: Springer, pp. 189–213.
  • Porter, R. C. (1967), “Extra-Point Strategy in Football,” The American Statistician, 21, 14–15. DOI: 10.2307/2682653.
  • Powell, J. L., Stock, J. H., and Stoker, T. M. (1989), “Semiparametric Estimation of Index Coefficients,” Econometrica, 57, 1403–1430. DOI: 10.2307/1913713.
  • Rapoport, A. (1966), Two-Person Game Theory: The Essential Ideas, Ann Arbor, MI: University of Michigan Press.
  • Reed, D. D., Critchfield, T. S., and Martens, B. K. (2006), “The Generalized Matching Law in Elite Sport Competition: Football Play Calling as Operant Choice,” Journal of Applied Behavior Analysis, 39, 281–297. DOI: 10.1901/jaba.2006.146-05.
  • Robbins, H. E. (1992), An Empirical Bayes Approach to Statistics, New York: Springer, pp. 388–394.
  • Romer, D. (2002), “It’s Fourth Down and What Does the Bellman Equation Say? A Dynamic Programming Analysis of Football Strategy,” Working paper 9024, National Bureau of Economic Research.
  • Sackrowitz, H. (2012), “Refining the Point(s)-after-Touchdown Decision,” CHANCE, 13, 29–34. DOI: 10.1080/09332480.2000.10542218.
  • Smith, A. F. M., and Roberts, G. O. (1993), “Bayesian Computation via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods,” Journal of the Royal Statistical Society, Series B, 55, 3–23. DOI: 10.1111/j.2517-6161.1993.tb01466.x.
  • Stacy, E. W. (1962), “A Generalization of the Gamma Distribution,” The Annals of Mathematical Statistics, 33, 1187–1192. DOI: 10.1214/aoms/1177704481.
  • Stern, H. S. (1998), “American Football,” in Statistics in Sports, ed. A. J. Bennett, London: Hodder Education Publishers.
  • The Athletic Staff. (2021), “Presbyterian Coach Kevin Kelley, Known for Rarely Punting, Resigns after 2-9 Record in First Season,” available at https://theathletic.com/news/presbyterian-coach-kevin-kelley-known-for-rarely-punting-resigns-after/2-9-record-in-first-season/LbFBFDQQSaFm/.
  • Tierney, L. (1994), “Markov Chains for Exploring Posterior Distributions,” The Annals of Statistics, 22, 1701–1728. DOI: 10.1214/aos/1176325750.
  • Yam, D., and Lopez, M. J. (2019), “What was Lost? A Causal Estimate of Fourth Down Behavior in the National Football League,” Journal of Sports Analytics, 5, 153–167. DOI: 10.3233/JSA-190294.
  • Yurko, R., Ventura, S., and Horowitz, M. (2019), “nflWAR: A Reproducible Method for Offensive Player Evaluation in Football,” Journal of Quantitative Analysis in Sports, 15, 163–183. DOI: 10.1515/jqas-2018-0010.

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