This Elo rating calculator computes rating changes after a match using the standard Elo algorithm. Enter both players' current ratings, the match result, and the K-factor to see updated ratings and win probabilities.
Match Details
Result
How to Use the Elo Rating Calculator
The Elo rating system calculates relative skill levels in zero-sum games. Developed by Arpad Elo for chess in the 1960s, it's now used in competitive games ranging from chess and Go to video games and sports rankings.
The Formula
Expected score for Player A: Ea = 1 / (1 + 10^((Rb - Ra) / 400)). After the match, new rating = old rating + K × (actual score - expected score). Actual score: 1 for a win, 0.5 for a draw, 0 for a loss. A 200-point difference means the higher-rated player wins about 76% of the time.
Choosing K-Factor
Higher K-factors cause bigger rating swings after each game — good for players who are still establishing their rating, but volatile for established players. K=32 is used for new players in most systems. K=16 or K=10 protects high-rated players from losing significant rating to random variance.
Limitations
Standard Elo works best in 1v1 games with clear win/loss outcomes. Team games, games with large skill gaps between teammates, and systems where players play very few games are all cases where variants like Glicko-2 perform better. Most modern video game ranking systems use proprietary algorithms that modify core Elo.
FAQ
Is this Elo calculator free?
Yes, completely free with no account required. All calculations happen in your browser.
What is the Elo rating system?
Elo is a method for calculating the relative skill levels of players in competitive games. Developed by Arpad Elo for chess, it's now used in video games, board games, sports rankings, and more. A higher Elo means a higher expected win rate against a given opponent.
What K-factor should I use?
K=32 for beginners and new players (ratings change quickly). K=24 for intermediate players with established ratings. K=16 for experienced players and official tournaments (ratings change slowly). FIDE chess uses K=40 for new players, K=20 for established players, K=10 for top players.
How is the expected score calculated?
The expected score for Player A is 1 / (1 + 10^((Rating_B - Rating_A) / 400)). This gives a probability between 0 and 1. Two players with the same rating each have a 50% expected score. A 200-point rating difference gives the higher-rated player about 76% expected win probability.
Does this work for video game MMR systems?
The calculator uses the standard Elo algorithm, which is accurate for games that explicitly use Elo. Games like League of Legends, Valorant, or Overwatch use proprietary MMR systems that modify the core Elo formula, so results are approximate for those games.