The elo Package

The elo package includes functions to address all kinds of Elo calculations.

library(elo)

It also includes comparable models for accuracy (auc, MSE) benchmarking (see, e.g., elo.glm() which fits a logistic regression model, elo.winpct() which fits a model based on win percentage, and elo.markovchain() which fits a Markov chain model). Please see the vignette for examples.

Naming Schema

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.