A simple library to rank players.

This package contains functions to rank players, given the results of their games.

For static rankings, where players don't change their skill-level, the Bradley-Terry model computes a score for each player that predicts the probability at which one player would win against another.

For dynamic rankings, where players change their skill-level over time, the ELO ranking system provides a score that dynamically adjust with the results of the players.

Usage

A simple usage example for Bradley-Terry:

import'package:ranking/ranking.dart';
main() {
// In the following list the first entry in the pair (representing a game)// won that game.var games = [
["Player 2", "Player 1"], // Player 2 won over Player 1.
["Player 2", "Player 3"],
["Player 3", "Player 2"],
["Player 3", "Player 2"],
];
var scores =computeBradleyTerryScores(games);
// The `scores` map contains a score for each player:// Player 1 -> 0.000// Player 2 -> 0.333// Player 3 -> 0.667
}

A simple usage example for ELO:

import'package:ranking/ranking.dart';
main() {
// The game-scope (3rd column) indicates the result of the game:// * 1.0: the first player won decisively.// * 0.5: a draw.// * 0.0: the second player won decisively.var games = [
["Player 2", "Player 1", 1.0],
["Player 3", "Player 2", 0.5],
["Player 3", "Player 1", 0.0],
["Player 3", "Player 2", 1.0],
["Player 2", "Player 3", 1.0],
];
var elo =newElo(
defaultInitialRating:100,
// With an `n` of 30, a difference of 30 in score means that the// stronger player is 10 times more likely to win.
n:30,
// How much new game-results move the score. With 10, players with// the same score will have a difference of 10 after a decisive// victory/loss.
kFactor:10
);
games.forEach((list) { elo.recordResult(list[0], list[1], list[2] asdouble); });
var ratings = elo.ratings;
// The `rating` map contains a rating for each player:// Player 1 -> 101// Player 2 -> 103// Player 3 -> 95
}

Features and bugs

Please file feature requests and bugs at the issue tracker.