Free chess tool

ELO Rating Calculator

See exactly how many rating points a game is worth before or after you play it.

Enter your rating, your opponent’s rating, the result, and the K-factor your rating system uses. The calculator shows your expected score, the points you’d gain or lose, and your new rating — recomputed as you type. It uses the standard ELO formula, the same math behind chess ratings on ChessTrophies and most federations.

Calculate a rating change

Expected score
Rating change
New rating

Expected score is your win probability (a draw counts as half). K-factor controls how fast ratings move.

Expected score vs. rating difference

A quick reference for how the rating gap maps to your expected score. A positive difference means you out-rate your opponent.

Rating difference (you − opponent)Your expected score

How ELO rating math works

ELO estimates each player’s strength as a single number. Before a game it predicts an expected score from the rating gap; after the game it nudges both ratings toward reality based on how the result compared to that prediction.

The expected score is:

E = 1 / (1 + 10^((opponent − you) / 400))

Your actual score S is 1 for a win, 0.5 for a draw, 0 for a loss. Your new rating is you + K · (S − E), rounded to the nearest whole point. Beat a stronger opponent and S − E is large and positive, so you gain a lot; lose to a weaker one and you drop more.

FAQ

What K-factor should I use?

Most casual and club systems use 32. Federations often lower K as you improve (24, then 16 for masters) so established ratings are stable, and raise it (40) for newcomers so their rating finds its level quickly.

Why do I gain more for beating a higher-rated player?

Because your expected score against them is low, so S − E is large. The upset is “surprising” to the formula, and it corrects your rating more.

Is a 400-point gap really 10-to-1 odds?

Roughly. A 400-point difference gives the favourite an expected score of about 0.91 — near a 10-to-1 edge. That is the anchor the whole scale is built around.

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