Elo Rating Calculator
Update a player's Elo after a match.
Results update as you type.
How it works
The Elo rating system, invented for chess and now used across countless games and sports, updates a player's rating after each match based on the result and the strength of the opponent. This Elo rating calculator performs that update. Enter your current rating, your opponent's rating, whether you won, drew, or lost, and the K-factor, and it returns your new rating and the points you gained or lost. Elo's elegance is that it rewards results in proportion to how surprising they are. Before the game, the system calculates your expected score from the rating difference: if you far outrate your opponent, you are expected to win comfortably, so beating them earns only a few points, while losing costs many. Upset a much stronger player and you gain a large chunk of rating. This self-correcting mechanism means ratings converge over time on a fair measure of skill, which is why the system underpins chess rankings, online matchmaking, and many sports models. The two-step calculation is simple to follow. First, the expected score comes from a logistic formula in which every 400 rating points corresponds to a tenfold change in the odds. Second, your rating shifts by the K-factor times the gap between your actual result and that expectation. The K-factor controls sensitivity: a high value makes ratings move quickly, suiting new or provisional players, while a low value keeps established ratings stable. Players, tournament organisers, and game designers can use this calculator to see exactly how a single result reshapes a rating.
new rating = rating + K × (result − expected); expected = 1 ÷ (1 + 10^((opp − rating) ÷ 400))
The Elo system first predicts your expected score against an opponent from the rating gap, using a logistic curve where a 400-point advantage means roughly a ten-to-one favourite. Your expected score sits between zero and one. After the game, your rating moves by the K-factor multiplied by the difference between your actual result and that expectation. Beating a stronger player, where you were expected to lose, gains many points; beating a weaker one, as expected, gains few.
Source:Elo rating system (Arpad Elo)
We review all our tools from time to time to ensure accuracy.
Worked example
How to use this calculator
- 1
Enter your values
Enter your rating, opponent rating and result.
- 2
Adjust the options
Adjust k-factor if they apply — sensible defaults are already set.
- 3
Read your result
New rating updates instantly as you type — no button to press.
Frequently asked questions
What is the expected score in Elo?
The expected score is the system's prediction of how you should perform against a given opponent, calculated from the difference in ratings and expressed as a number between zero and one. Against an equal opponent it is 0.5; against a much stronger one it is close to zero; against a much weaker one, close to one. Your rating change depends on how your actual result compares to this expectation.
What is the K-factor and what value should I use?
The K-factor sets how much a single game can change your rating. A higher K, such as 40, moves ratings quickly and suits new or provisional players still finding their level, while a lower K, such as 10 or 20, keeps established and elite ratings stable. Chess federations commonly use 32 for most players, so 32 is a sensible default here unless your specific system prescribes another value.
Why do I gain more points for beating a stronger player?
Because Elo rewards results relative to expectation. When you face a higher-rated opponent, the system expects you to lose, so your expected score is low. Winning produces a large gap between your actual result of one and that low expectation, and multiplying by the K-factor yields a big rating gain. Conversely, beating a much weaker opponent, which was expected, produces a small gap and only a modest gain.
How does a 400-point rating difference translate to odds?
In the Elo formula, every 400 rating points corresponds to a tenfold change in the expected odds. A player rated 400 points above another is expected to score about ten times as often, giving an expected score near 0.91. This logarithmic scaling is why the gap between 2000 and 2400 represents a far larger skill difference in practice than the raw 400-point number alone might suggest to a newcomer.
Does Elo work for games other than chess?
Yes. Although Arpad Elo designed the system for chess, its logic applies to any head-to-head competition with wins, losses, and draws. Video game matchmaking, tennis and football rating models, board games, and esports ladders all use Elo or close variants. The core idea, adjusting ratings by the difference between actual and expected results, is general, so this calculator works for any two-player contest you can express as a win, draw, or loss.