TrueSkill Rating Calculator

June 25, 2026
/ Table Games Calculator
/ By Tablegameshub

TrueSkill Rating Calculator

Estimate TrueSkill-style rating movement from mu, sigma, beta, tau, draw probability, match result, and team average comparison.

🎯Presets

⚙Rating Inputs

This is a compact TrueSkill approximation for table ratings. It uses mu as skill mean, sigma as uncertainty, beta for game variance, tau for drift, draw probability for draw margin, and mu - 3 sigma as conservative rating.

Match result Choose the reported table result before updating ratings. Players per team Extra player fields are included in team totals only when selected. Beta skill spread Default TrueSkill beta is 25 / 6, about 4.167. Tau dynamics factor Tau adds uncertainty before the match update. Draw probability Used to approximate the draw margin around equal teams. Conservative multiplier The common leaderboard display is conservative rating = mu - 3 sigma.

👥Team A Ratings

Team A player 1 mu Skill mean for Team A player 1. Team A player 1 sigma Uncertainty for Team A player 1. Team A player 2 mu Used when players per team is 2 or more. Team A player 2 sigma Used when players per team is 2 or more. Team A player 3 mu Used when players per team is 3 or more. Team A player 3 sigma Used when players per team is 3 or more. Team A player 4 mu Used when players per team is 4. Team A player 4 sigma Used when players per team is 4.

👥Team B Ratings

Team B player 1 mu Skill mean for Team B player 1. Team B player 1 sigma Uncertainty for Team B player 1. Team B player 2 mu Used when players per team is 2 or more. Team B player 2 sigma Used when players per team is 2 or more. Team B player 3 mu Used when players per team is 3 or more. Team B player 3 sigma Used when players per team is 3 or more. Team B player 4 mu Used when players per team is 4. Team B player 4 sigma Used when players per team is 4.

Calculated TrueSkill Results

Team A Conservative

0.00

mu - 3 sigma average

Team B Conservative

0.00

mu - 3 sigma average

Expected Winner

Even

pre-match comparison

Draw Margin

0.00

rating points

🧮Current Math Grid

25.00

Team A Avg Mu

25.00

Team B Avg Mu

0.00

Average Gap

50.0%

A Win Estimate

📊Dynamic Rating Tables

Player	Old mu	Old sigma	New mu	New sigma	mu - 3 sigma
A1	25.00	8.33	25.00	8.33	0.00

Team	Total mu	Average mu	Team sigma	Avg conservative	Comparison
Team A	25.00	25.00	8.33	0.00	Even

Scenario	Result Tested	Performance Gap	V Factor	W Factor	Read
Current	A wins	0.00	0.00	0.00	Even

📖TrueSkill Reference Tables

Parameter	Common Default	What It Changes	Practical Use
mu	25.000	Center of rating estimate	Higher mu means higher estimated skill.
sigma	8.333	Uncertainty around mu	High sigma moves faster after results.
beta	4.167	Game-to-game performance spread	Higher beta softens upset impact.
tau	0.083	Rating drift before each match	Use more tau when skills change often.
Draw probability	10%	Draw margin width	Higher values make draws less surprising.

Preset	Team Size	Key Question	Expected Movement
Fresh 1v1 Match	1v1	How do defaults move?	Moderate, symmetric update.
Favored Player Upset	1v1	How big is an upset?	Large winner gain, favored loss.
Balanced 2v2	2v2	How are team wins shared?	Uncertain players move more.
Close Rated Draw	1v1	What does a draw do?	Ratings pull toward each other.

Conservative Rating	Formula	Meaning	Leaderboard Read
Standard	mu - 3 sigma	Skill estimate with uncertainty penalty	New players start low despite mu 25.
Loose	mu - 2 sigma	Less penalty for uncertainty	Useful for casual ladders.
Strict	mu - 3 sigma	Requires confidence to climb	Useful for competitive ladders.
Team average	avg(mu - k sigma)	Average safe rating by team	Highlights roster balance.

💡Table Tips

Uncertainty tip: Compare mu and sigma together. A player with high mu and high sigma may still have a low conservative rating because the system is not confident yet.

Team tip: Team totals decide the update, but each player receives movement scaled by their sigma squared, so uncertain teammates absorb more rating change.

TrueSkill ratings exists in order to provide a method of converting game results to skill ratings. A single game result dont provide a person with much information about their skill, and a single game result is not enough to determine the skill of a player. TrueSkill ratings help to provide information about the result of a single game by comparing that result to the results of all previous games by that player.

Therefore, the TrueSkill system accounts for the fact that a player’s skill can be uncertain. The TrueSkill system treats each TrueSkill rating as two numbers rather than one. One number is a best guess at a players skill, and the other number is a measurement of how much that best guess could potentially be incorrect.

How TrueSkill Ratings Work

When game results occurs, the system updates the skill and uncertainty ratings for each player at the same time. If a player win a game against another player with a lower skill, the winning player’s skill is incremented and the uncertainty in that skill is decrease. If a player lose a game, their skill and uncertainty both decrease.

If a game ends in a draw, the players’ skills are both pulled towards each other; however, there is no large change in either player’s skill. The change in each player’s skill is based off the uncertainty band for each player. Players with large uncertainty bands will experience a greater change in their skill than players with small uncertainty bands.

Many leaderboards do not include the skill guess for each player, but instead display a conservative rating. A conservative rating is calculated by taking a player’s skill and subtracting some multiple of the uncertainty from that skill. A player that have few games played for their skill will likely have a high skill guess but very little uncertainty.

By subtracting a multiple of the uncertainty, the skill of other players will not be too impacted by a player with few games played. Therefore, this is one way in which the system can penalize players for having few games played. A calculator can be used to determine the change in conservative ratings if the multiplier is changed.

This can help to determine whether a ladder should be more generous or more strict toward new players. In the case of team games, the system require performing additional steps beyond those for individual players. The system does not consider each player in the team as having separate skill.

Instead, the system calculates an average skill for the team and an uncertainty in that average skill. Based upon the outcome of the game, the system calculates individual changes to each player’s skill. Players that have played fewer games will experience larger changes in their skill than players that have high level of certainty in their skill.

Thus, when players that are new to a team sport experience a winning or losing team, their changes in ranking will be faster than for more experienced players. The draw probability for a game can be set to be high or low. A high draw probability will cause the system to treat matches between players of similar skills as draws, but lower draw probabilities will treat those same games as having a clear winner and loser.

For some games, such as chess, draws are very common, but in other games draws may be very rare. Thus, the draw probability should be adjusted to account for these different games. A calculator can be used to view the changes in skill if the draw margin is changed.

The beta parameter can be used to determine how much a player’s skill can vary from game to game. High values of the beta parameter will cause most games to have high levels of noisy outcomes, whereas low values of the beta parameter indicate that the better player will win the majority of games against players of lesser skill. This value can be adjusted to account for the common occurrence of upsets in a population of players.

The tau parameter is a small drift term that is used to ensure that a player’s rating does not remain frozen once they stop playing. If tau were 0, a player who stopped playing would retain their current skill level for the rest of time. Instead, the uncertainty in a player’s skill increases over time.

This means that when a player returns to playing games, their early games will have more weight than if they had simply returned to the game after taking a short break. These parameters can all be adjusted. Microsoft published the default parameters for the system, and these are the parameters that is used in the Xbox platform for matchmaking.

The other parameters can be adjusted, but each parameter should be adjusted one at a time so that the effect on conservative ratings and update size can be determined. If new players are climbing too quickly in rank, then the conservative multiplier should be increased. Draw probabilities can be increased if there are too many draws between skilled players, or decreased if there are too many games that have clear winners and losers.

For veterans who have not played for many months, their skill should be adjusted to update if the tau parameter is increased. The values of these parameters is important to understand how the system is functioning. Each adjustment to a player’s games can be simulated with the system, and the outcomes of those games can be used to understand if a change to the ladder is beneficial.

These numbers can be used to determine the balance of each team prior to each game. Thus, incorporating these ratings can remove the guesswork in determining team balance. A TrueSkill rating is not just a single number, but it is a skill rating and a measurement of how much that rating could potentially be incorrect.

The fact that both of these numbers are provided for each player is what ensures that the system is honest and does not provide inaccurate rating to players.