Scales globally

Elo

The original chess rating. Predict the result from the ratings gap, then correct by how wrong the prediction was — beat someone above you and yours jumps.

FamilyElo-like

What does a rating gap mean?

Interactive example · no real player data

Expected score50%

Your rating minus opponent’s0

Equal ratings split the expectation 50/50. Expected score includes draws; it is not a guaranteed win rate.

How it works About 1 min read

Elo is the most famous rating system in the world, created by Arpad Elo for chess in the 1960s. It estimates player skill using pairwise win/loss outcomes and predicts future match results.

How it works: Each player starts with a rating (default 1500). After a match, the winner gains points and the loser loses points. The amount exchanged depends on the rating difference: beating a higher-rated opponent earns more points, while losing to a lower-rated one costs more. The K-factor controls how responsive ratings are.

When to use it: The gold standard for 1v1 games with established player pools. Its predictions improve with more matches, and it naturally creates an intuitive skill ladder.

Watch out for: Only supports 1v1 or team-vs-team (not FFA). Doesn't model uncertainty like Glicko-2 or TrueSkill. Ratings can be slow to converge for new players without a provisional K-factor period.

Will it fit your results?

Works well with

Games whose results this method reads cleanly

Chess Go Tennis Table Tennis

Also in Elo-like

Adaptive skill ratings that update after every match.

Multiplayer EloLong histories with a stable group and mixed table sizes — the default serious choice, and it scales to global boards.