This function returns the win, loss, and push probabilities of a given bet based on the current line and your predicted line.
Arguments
- pred_spread
Predicted spread for the team you want to bet on
- spread
Spread for the team that you want to bet on (-3.5, -7, 4, 2.5)
- sport
Sport/League of the teams being bet on. Possible values are:
NBA
, National Basketball AssociationNCAAB
, College BasketballNFL
, National Football LeagueNCAAF
, College Football
Value
probs Plot of the simulation as well as the percentage of simulations that were positive and negative.
References
Stern, Hal. "The Probability of Winning a Football Game as a function of the Pointspread." The American Statistician 45, no. 3 (1991): 179-83. Accessed July 18, 2020. doi:10.2307/2684286. https://statistics.stanford.edu/sites/g/files/sbiybj6031/f/COV%20NSF%2059.pdf
Stern, Hal. "On the Probability of Winning a Football Game." The American Statistician 45, no. 3 (1991): 179-83. Accessed July 18, 2020. doi:10.2307/2684286. https://www-jstor-org.turing.library.northwestern.edu/stable/2684286
Winston, Wayne L. "From Point Ratings to Probabilities." In Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football, 290-97. PRINCETON; OXFORD: Princeton University Press, 2009. Accessed July 18, 2020. doi:10.2307/j.ctt7sj9q.48.
Examples
bet_prob(-9, -3.5, sport = "NFL")
#> Win.Probability Lose.Probability Push.Probability
#> 1 0.6542519 0.3457481 0
bet_prob(-7, -3, sport = "NBA")
#> Win.Probability Lose.Probability Push.Probability
#> 1 0.6147293 0.3538302 0.03144052
bet_prob(21, 10.5, sport = "NCAAF")
#> Win.Probability Lose.Probability Push.Probability
#> 1 0.2558316 0.7441684 0
bet_prob(-3, 5, sport = "NCAAB")
#> Win.Probability Lose.Probability Push.Probability
#> 1 0.7733726 0.1976625 0.02896481