An implementation of the Glicko-2 rating system for Scala and Scala.js.

Add the dependency in the build.sbt file.

libraryDependencies += "com.github.mrdimosthenis" %% "glicko2" % "1.0.1"

For Scala.js use the %%% operator instead of %%.

import dimos.glicko2._

Player is a case class with three parameters (rating, deviation, volatility).

• We can create a player by defining their parameters.

val player = Player(1464, 151, 0.06)

• We can also create a player with the default initial parameters.

val newPlayer = Player.newEntry()
// Player(1500.0, 350.0, 0.06)

Result is an enum with three values (WonAgainst, DefeatedBy, TiedWith).

To create results, we need to specify their kind, their opponent and place them inside a Seq.

val res = List(Result.WonAgainst(newPlayer))

We can see how results affect a player.

val playerUpdated = player.afterPeriod(res)
// Player(1507.5, 145.3, 0.06)

Suppose a player rated 1500 competes against players rated 1400, 1550 and 1700, winning the first game and losing the next two. Assume the 1500-rated player’s rating deviation is 200, and his opponents’ are 30, 100 and 300, respectively. Assume the 1500 player has volatility σ = 0.06, and his opponents have 0.07, 0.08 and 0.05, respectively.

Let's see how this example is translated and what happens to the first player when the period ends.

val p = Player(1500, 200, 0.06)
val opp1 = Player(1400, 30, 0.07)
val opp2 = Player(1550, 100, 0.08)
val opp3 = Player(1700, 300, 0.05)
val res1 = Result.WonAgainst(opp1)
val res2 = Result.DefeatedBy(opp2)
val res3 = Result.DefeatedBy(opp3)
val results = List(res1, res2, res3)
val pUpdated = p.afterPeriod(results)
// Player(1464.06, 151.52, 0.05999)

If the default values of the system do not serve us well, we can change them.

val tuning = Tuning.default(initRating = 1200, minDeviation = 30, tau = 0.75)
// Tuning(1200.0, 350.0, 30.0, 0.06, 0.75, 0.000001)

In that case, we need to pass tuning as a parameter to newEntry and afterPeriod functions.

These are the parameters of Tuning and their default values:

• initRating: 1500
• maxDeviation: 350,
• minDeviation: 0,
• initVolatility: 0.06
• tau: 0.5
• tolerance: 0.000001