We illustrate through a case study that regressive prediction is the best method to forecast sports outcomes. By taking predictions of promotion to first division soccer from a mathematician from one of the most famous sports websites in Brazil, we show that making Bayesian updates is misleading when we expect regression to the mean. The expert failed to realize that the more extreme the results are, the more regression is expected, because extremely good scores suggest very lucky days.
Cite this paper
Silva, M. and Silva, S. D. (2019). Regressive Prediction Is the Best Way to Forecast Sports Outcomes: Evidence from Brazilian Soccer. Open Access Library Journal, 6, e5264. doi: http://dx.doi.org/10.4236/oalib.1105264.
Aoki, R.Y.S., Assuncao, R.M. and De Melo, P.O.S.V. (2017) Luck Is Hard to Beat: The Difficulty of Sports Prediction. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, 13-17 August 2017, 1367-1376. https://doi.org/10.1145/3097983.3098045
Da Silva, S., Matsushita, R. and Silveira, E. (2013) Hidden Power Law Patterns in the Top European Football Leagues. Physica A: Statistical Mechanics and Its Applications, 392, 5376-5386. https://doi.org/10.1016/j.physa.2013.07.008
Pluchino, A., Biondo, A.E. and Rapisarda, A. (2018) Talent versus Luck: The Role of Randomness in Success and Failure. Advances in Complex Systems, 21, 1-31. https://doi.org/10.1142/S0219525918500145
Kahneman, D. and Tversky, A. (1982) Intuitive Prediction: Biases and Corrective Procedures. In: Kahneman, D., Slovic, P. and Tversky, A., Eds., Judgment under Uncertainty: Heuristics and Biases, Cambridge University Press, Cambridge, 414-421. https://doi.org/10.1017/CBO9780511809477.031
