Ranking Teams by Elo Rating and Comparable Methods
Post-update Elo values
Compute a Colley matrix model for a matchup.
Calculate AUC on an elo.run object
Compute a (usually logistic) regression model for a series of matches.
Compute a Markov chain model for a series of matches.
Interpret formulas in elo functions
Create a "margin of victory" column
Calculate the mean square error
Elo probability
The Elo Package
Helper functions for elo.run
Calculate running Elos for a series of multi-team matches.
Calculate running Elos for a series of matches.
Elo updates
Compute a (usually logistic) regression based on win percentage for a ...
Classify teams that are favored to win
Extract model values
Details on elo formulas and the specials therein
Make Predictions on an elo Object
Rank teams
Create a 1/0/0.5 win "indicator"
Summarize an elo Object
A flexible framework for calculating Elo ratings and resulting rankings of any two-team-per-matchup system (chess, sports leagues, 'Go', etc.). This implementation is capable of evaluating a variety of matchups, Elo rating updates, and win probabilities, all based on the basic Elo rating system. It also includes methods to benchmark performance, including logistic regression and Markov chain models.
Useful links