ELo Rating System
The Elo rating system is a method for calculating the relative skill levels of players in competitor-versus-competitor/ two player games such as chess. It is named after its creator Arpad Elo, a Hungarian-born American physics professor and a amateur chess player himself. The Elo system was invented as an improved chess rating system, but today it is also used in many other games. It is also used as a rating system for multiplayer competition in a number of video games, and has been adapted to team sports including association football, American college football, basketball, Major League Baseball, and eSports. Elo's system was adopted by the World Chess Federation (FIDE) in 1970. It replaced Harkness rating system, also a numerical ratings system, devised by Kenneth Harkness, to allow members to track their individual progress in terms other than tournament wins and losses.
Each player has a numerical rating. A higher number indicates a better player, based on results against other rated players. The winner of a contest between two players gains a certain number of points in his or her rating and the losing player loses the same amount. The number of points won or lost in a contest depends on the difference in the ratings of the players, so a player will gain more points by beating a higher-rated player than by beating a lower-rated player. In chess, for instance, if player A is rated 100 points higher than player B, it is expected that player A will win about five out of eight games played. Over a series of games if either player does better than expected his or her rating will go up.
Elo's system replaced earlier systems of competitive rewards with a system based on statistical estimation. Rating systems for many sports award points in accordance with subjective evaluations of the 'greatness' of certain achievements. For example, winning an important golf tournament might be worth an arbitrarily chosen five times as many points as winning a lesser tournament. A statistical endeavor, by contrast, uses a model that relates the game results to underlying variables representing the ability of each player.