Elo Rating Calculator
Experiment with different Elo rating parameters to see how they affect rating changes. Adjust player ratings, match outcomes, and system parameters to simulate different scenarios.
Match Setup
Controls rating change volatility
Affects expected outcome probability
Reduces rating losses by this %
Match Preview
Adjust settings and calculate to see rating changes
Rating formula
Rating change vs opponent rating difference (updates live as you edit settings, includes capping)
This calculator demonstrates the Elo rating system used by Team Up's leaderboard bot.
How It Works
Expected Outcome
The system calculates the probability of each player winning based on their rating difference. Higher-rated players are expected to win more often.
Rating Adjustment
Upsets (underdog wins) cause larger rating swings. Expected outcomes cause smaller changes. The K-factor controls the overall magnitude.
Quick Guide
- 1 Enter Player and Opponent Ratings, or switch to FFA mode to add multiple players
- 2 Select the Match Result (1v1) or assign Placements (FFA)
- 3 Click Calculate to see the rating changes for all players
- 4 Expand Core Elo Settings to adjust K-factor, influence range, and more
Learn How Elo Works
Watch these videos for an in-depth look at the math and theory behind the Elo rating system.
Key Parameters
K-Factor
Default: 32Controls rating volatility. Higher values mean bigger rating swings per match.
Influence Range
Default: 400The rating difference at which win probability shifts significantly. A 400-point difference gives the favorite ~91% expected win rate.
Loss Dampen
Default: 0%Reduces rating losses by a percentage. Useful if you want to soften the impact of losses while keeping win rewards the same.
FFA Distribution
Default: OnIn Free-for-All matches, each player is compared against every opponent pairwise. When enabled, the total rating change is divided by the number of opponents, keeping FFA rating changes on the same scale as 1v1 matches.
Rating Capping
Default: OffLimits extreme rating changes when skill gaps are large. Prevents favorites from gaining almost nothing for expected wins or underdogs from losing almost nothing for expected losses.
Example Scenarios
Even Match
Two players with equal ratings (1200 vs 1200)
Expected Win
Favorite wins (1400 beats 1200)
Upset
Underdog wins (1200 beats 1400)
Values shown use default settings (K-factor: 32, Influence Range: 400)
Put these ratings to work
This calculator runs the exact same Elo engine as the Team Up bot. Add it to your Discord server and every setting above is yours to tune per leaderboard.