private static Rating CalculateNewRating(GameInfo gameInfo, Rating selfRating, Rating opponentRating,
PairwiseComparison comparison)
{
double drawMargin = DrawMargin.GetDrawMarginFromDrawProbability(gameInfo.DrawProbability, gameInfo.Beta);
double c =
Math.Sqrt(
Square(selfRating.StandardDeviation)
+
Square(opponentRating.StandardDeviation)
+
2 * Square(gameInfo.Beta));
double winningMean = selfRating.Mean;
double losingMean = opponentRating.Mean;
switch (comparison)
{
case PairwiseComparison.Win:
case PairwiseComparison.Draw:
// NOP
break;
case PairwiseComparison.Lose:
winningMean = opponentRating.Mean;
losingMean = selfRating.Mean;
break;
}
double meanDelta = winningMean - losingMean;
double v;
double w;
double rankMultiplier;
if (comparison != PairwiseComparison.Draw)
{
// non-draw case
v = TruncatedGaussianCorrectionFunctions.VExceedsMargin(meanDelta, drawMargin, c);
w = TruncatedGaussianCorrectionFunctions.WExceedsMargin(meanDelta, drawMargin, c);
rankMultiplier = (int)comparison;
}
else
{
v = TruncatedGaussianCorrectionFunctions.VWithinMargin(meanDelta, drawMargin, c);
w = TruncatedGaussianCorrectionFunctions.WWithinMargin(meanDelta, drawMargin, c);
rankMultiplier = 1;
}
double meanMultiplier = (Square(selfRating.StandardDeviation) + Square(gameInfo.DynamicsFactor)) / c;
double varianceWithDynamics = Square(selfRating.StandardDeviation) + Square(gameInfo.DynamicsFactor);
double stdDevMultiplier = varianceWithDynamics / Square(c);
double newMean = selfRating.Mean + (rankMultiplier * meanMultiplier * v);
double newStdDev = Math.Sqrt(varianceWithDynamics * (1 - w * stdDevMultiplier));
return(new Rating(newMean, newStdDev));
}
private static void UpdatePlayerRatings <TPlayer>(GameInfo gameInfo,
IDictionary <TPlayer, Rating> newPlayerRatings,
IDictionary <TPlayer, Rating> selfTeam,
IDictionary <TPlayer, Rating> otherTeam,
PairwiseComparison selfToOtherTeamComparison)
{
double drawMargin = DrawMargin.GetDrawMarginFromDrawProbability(gameInfo.DrawProbability, gameInfo.Beta);
double betaSquared = Square(gameInfo.Beta);
double tauSquared = Square(gameInfo.DynamicsFactor);
int totalPlayers = selfTeam.Count() + otherTeam.Count();
double selfMeanSum = selfTeam.Values.Sum(r => r.Mean);
double otherTeamMeanSum = otherTeam.Values.Sum(r => r.Mean);
double c = Math.Sqrt(selfTeam.Values.Sum(r => Square(r.StandardDeviation))
+
otherTeam.Values.Sum(r => Square(r.StandardDeviation))
+
totalPlayers * betaSquared);
double winningMean = selfMeanSum;
double losingMean = otherTeamMeanSum;
switch (selfToOtherTeamComparison)
{
case PairwiseComparison.Win:
case PairwiseComparison.Draw:
// NOP
break;
case PairwiseComparison.Lose:
winningMean = otherTeamMeanSum;
losingMean = selfMeanSum;
break;
}
double meanDelta = winningMean - losingMean;
double v;
double w;
double rankMultiplier;
if (selfToOtherTeamComparison != PairwiseComparison.Draw)
{
// non-draw case
v = TruncatedGaussianCorrectionFunctions.VExceedsMargin(meanDelta, drawMargin, c);
w = TruncatedGaussianCorrectionFunctions.WExceedsMargin(meanDelta, drawMargin, c);
rankMultiplier = (int)selfToOtherTeamComparison;
}
else
{
// assume draw
v = TruncatedGaussianCorrectionFunctions.VWithinMargin(meanDelta, drawMargin, c);
w = TruncatedGaussianCorrectionFunctions.WWithinMargin(meanDelta, drawMargin, c);
rankMultiplier = 1;
}
foreach (var teamPlayerRatingPair in selfTeam)
{
Rating previousPlayerRating = teamPlayerRatingPair.Value;
double meanMultiplier = (Square(previousPlayerRating.StandardDeviation) + tauSquared) / c;
double stdDevMultiplier = (Square(previousPlayerRating.StandardDeviation) + tauSquared) / Square(c);
double playerMeanDelta = (rankMultiplier * meanMultiplier * v);
double newMean = previousPlayerRating.Mean + playerMeanDelta;
double newStdDev =
Math.Sqrt((Square(previousPlayerRating.StandardDeviation) + tauSquared) * (1 - w * stdDevMultiplier));
newPlayerRatings[teamPlayerRatingPair.Key] = new Rating(newMean, newStdDev);
}
}
