elo.prob: Elo probability

Description

Calculate the probability that team A beats team B. This is vectorized.

Usage

elo.prob(elo.A, ...)
# S3 method for default
elo.prob(elo.A, elo.B, ..., elos = NULL, adjust.A = 0, adjust.B = 0)
# S3 method for formula
elo.prob(formula, data, na.action, subset, ..., elos = NULL)
# S3 method for elo.multiteam.matrix
elo.prob(elo.A, ..., elos = NULL)

Value

A vector of Elo probabilities.

Arguments

elo.A, elo.B: Numeric vectors of elo scores, or else vectors of teams.
...: Other arguments (not in use at this time).
elos: An optional named vector containing Elo ratings for all teams in formula or elo.A and elo.B.
adjust.A, adjust.B: Numeric vectors to adjust elo.A and elo.B by.
formula: A formula. See the help page for formulas for details.
data: A data.frame in which to look for objects in formula.
na.action: A function which indicates what should happen when the data contain NAs.
subset: An optional vector specifying a subset of observations.

Details

Note that formula can be missing the wins.A component. If present, it's ignored by elo.model.frame.

Examples

Run this code

elo.prob(1500, 1500)
elo.prob(c(1500, 1500), c(1500, 1600))

dat <- data.frame(wins.A = c(1, 0), elo.A = c(1500, 1500),
                  elo.B = c(1500, 1600), k = c(20, 20))
elo.prob(~ elo.A + elo.B, data = dat)

## Also works to include the wins and k:
elo.prob(wins.A ~ elo.A + elo.B + k(k), data = dat)

## Also allows teams
elo.prob(c("A", "B"), c("C", "C"), elos = c(A = 1500, B = 1600, C = 1500))