nfl_moneyline_cdf: Monte-Carlo estimates of moneyline distribution

In shill1729/sportsbets: Sports betting modeling and analysis

Monte-Carlo estimates of moneyline distribution

Description

Compute via Monte-Carlo simulations the probability of money-line events for a given favorite and underdog team. See the details documentation for the total cdf for more details on the model.

Usage

nfl_moneyline_cdf(fav_means, underdog_means, n = 10^6)

Arguments

fav_means	vector of mean number of touchdowns and (good) field goals of favorite team
underdog_means	vector of mean number of touchdowns and (good) field goals of underdog team
n	number of variates to use in Monte-Carlo estimate

Value

data.frame of favorite win chance and underdog win(+tie) chance.

shill1729/sportsbets documentation built on Dec. 27, 2022, 10:53 p.m.