The elo
package includes functions to address all kinds of Elo calculations.
-
elo.prob()
: calculate probabilities based on Elo scores -
elo.update()
: calculate Elo updates -
elo.calc()
: calculate post-update Elo values -
elo.run()
andelo.run.multiteam()
: calculate "running" Elo values for a series of matches
It also includes comparable models for accuracy (auc, MSE) benchmarking:
-
elo.glm()
which fits a logistic regression model -
elo.markovchain()
which fits a Markov chain model -
elo.colley()
for a method based on the Colley matrix. -
elo.winpct()
which fits a model based on win percentage
Please see the vignettes for examples.
Most functions begin with the prefix "elo.", for easy autocompletion.
-
Vectors or scalars of Elo scores are denoted "elo.A" or "elo.B".
-
Vectors or scalars of wins by team A are denoted by "wins.A".
-
Vectors or scalars of win probabilities are denoted by "p.A".
-
Vectors of team names are denoted "team.A" or "team.B".