Glicko rating system
Encyclopedia
The Glicko rating system and the Glicko-2 rating system are chess rating systems similar to the Elo rating system
Elo rating system
The Elo rating system is a method for calculating the relative skill levels of players in two-player games such as chess. It is named after its creator Arpad Elo, a Hungarian-born American physics professor....

: a method for assessing a player's strength in games of skill such as chess
Chess
Chess is a two-player board game played on a chessboard, a square-checkered board with 64 squares arranged in an eight-by-eight grid. It is one of the world's most popular games, played by millions of people worldwide at home, in clubs, online, by correspondence, and in tournaments.Each player...

. It was invented by Mark Glickman as an improvement of the Elo rating system. Glickman's principal contribution to measurement is "ratings reliability", called RD, for ratings deviation
Standard deviation
Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" there is from the average...

.

A higher Glicko rating implies more skill playing chess.

Both Glicko and Glicko-2 rating systems are under public domain and found implemented on game server
Game server
A game server is a remotely or locally run server used by game clients to play multiplayer video games. Most video games played over the Internet operate via a connection to a game server...

s online (like Free Internet Chess Server
Free Internet Chess Server
The Free Internet Chess Server is a volunteer-run Internet chess server. It was organised as a free alternative to the Internet Chess Club , after that site began charging for membership.-History:...

, Chess.com
Chess.com
Chess.com is an online chess community with over 4 million members as of October 2011. Chess.com has free chess play and contains a range of activities for its users, including tournaments, articles, videos, and social tools...

 and SchemingMind
SchemingMind
SchemingMind is a privately owned international correspondence chess club founded in 2002. Most games and tournaments are played on a correspondence chess server owned by the club for this purpose....

). The formulas used for the systems can be found on the Glicko website.

The RD measures the accuracy of a player's rating. For example, a player with a rating of 1500 and an RD of 50 has a real strength between 1400 and 1600 with 95% confidence. Twice the RD is added and subtracted from their rating to calculate this range. After a game, the amount the rating changes depends on the RD: the change is smaller when the player's RD is low (since their rating is already considered accurate), and also when their opponent's RD is high (since the opponent's true rating is not well known, so little information is being gained). The RD itself decreases after playing a game, but it will increase slowly over time of inactivity.

The Glicko-2 rating system improves upon the Glicko rating system and further introduces the rating volatility σ. A very slightly modified version of the Glicko-2 rating system is implemented by the Australian Chess Federation
Australian Chess Federation
The Australian Chess Federation is dedicated to promoting the game of chess in Australia, and is a member of FIDE, the world chess federation...

.

Step 1: determine RD

The new Ratings Deviation () is found using the old Ratings Deviation ():



Where is the amount of time (rating periods) since the last competition and '350' is assumed to be the RD of an unrated player. If several games have occurred within one rating period, the method treats them as having happened simultaneously. The rating period may be as long as several months or as short as a few minutes, according to how frequently games are arranged. The constant is based on the uncertainty of a player's skill over a certain amount of time. It can be derived from a thorough data analysis, or estimated by considering the length of time that would have to pass before a player's rating deviation would grow to that of an unrated player. If it assumed that it would take 100 rating periods for a player's rating deviation to return to an initial uncertainty of 350, and a typical player has a rating deviation of 50 then the constant can be found by solving
for .

Step 2: determine rating

The new ratings, after a series of m games, are determined by the following equation:



Where the following is defined:

let

let

let

let

represents the ratings of the individual opponents.

represents the outcome of the individual games. A win is 1, a draw is , and a loss is 0.

Step 3: determine new ratings deviation

The function of the prior RD calculation was to increase the RD appropriately to account for the increasing uncertainty in a player's skill level during a period of non-observation by the model. Now, the RD is updated (decreased) after the series of games:


External links

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