brackt/app/services/simulations/__tests__/wnba-simulator.test.ts

import { describe, it, expect } from "vitest";
import { srsToElo, simSeriesN, resolveElo } from "../wnba-simulator";
import { eloWinProbability } from "~/services/probability-engine";

// ─── srsToElo ─────────────────────────────────────────────────────────────────

describe("srsToElo", () => {
  it("maps SRS 0 to league-average Elo 1500", () => {
    expect(srsToElo(0)).toBe(1500);
  });

  it("maps positive SRS above 1500", () => {
    expect(srsToElo(5)).toBe(1600);
    expect(srsToElo(10)).toBe(1700);
  });

  it("maps negative SRS below 1500", () => {
    expect(srsToElo(-5)).toBe(1400);
    expect(srsToElo(-10)).toBe(1300);
  });

  it("is linear with scale 20", () => {
    expect(srsToElo(3)).toBe(srsToElo(1) + 40);
  });
});

// ─── eloWinProbability ────────────────────────────────────────────────────────

describe("eloWinProbability", () => {
  it("returns 0.5 for equal Elo ratings", () => {
    expect(eloWinProbability(1500, 1500)).toBeCloseTo(0.5, 6);
  });

  it("favors the higher-rated team", () => {
    expect(eloWinProbability(1600, 1500)).toBeGreaterThan(0.5);
    expect(eloWinProbability(1500, 1600)).toBeLessThan(0.5);
  });

  it("is anti-symmetric: P(A>B) + P(B>A) = 1", () => {
    const p = eloWinProbability(1640, 1430);
    expect(p + eloWinProbability(1430, 1640)).toBeCloseTo(1.0, 10);
  });

  it("SRS +10 vs SRS -10 gives ~76% win probability", () => {
    // srsToElo(+10) = 1700, srsToElo(-10) = 1300 → gap 400 → P = 1/(1+10^(-1)) ≈ 0.909
    // Actually gap of 400 → P ≈ 0.909. Let's verify the ±10 SRS case:
    // srsToElo(+10) = 1700, srsToElo(-10) = 1300 → gap = 400 → P ≈ 0.909
    const p = eloWinProbability(srsToElo(10), srsToElo(-10));
    expect(p).toBeGreaterThan(0.9);
    expect(p).toBeLessThan(0.92);
  });

  it("SRS +5 vs SRS 0 gives ~64% win probability", () => {
    // srsToElo(+5) = 1600, srsToElo(0) = 1500 → gap = 100 → P = 1/(1+10^(-0.25)) ≈ 0.640
    const p = eloWinProbability(srsToElo(5), srsToElo(0));
    expect(p).toBeGreaterThan(0.63);
    expect(p).toBeLessThan(0.66);
  });
});

// ─── resolveElo ───────────────────────────────────────────────────────────────

describe("resolveElo", () => {
  it("SRS mode with SRS present: uses SRS-derived Elo", () => {
    expect(resolveElo(5, 1600, true)).toBe(srsToElo(5)); // 1600
  });

  it("SRS mode with no SRS: falls back to futures Elo", () => {
    expect(resolveElo(null, 1620, true)).toBe(1620);
  });

  it("SRS mode with no SRS and no futures: falls back to 1500", () => {
    expect(resolveElo(null, null, true)).toBe(1500);
  });

  it("futures mode: uses futures Elo regardless of SRS", () => {
    expect(resolveElo(8, 1650, false)).toBe(1650);
  });

  it("futures mode with no futures: falls back to 1500", () => {
    expect(resolveElo(8, null, false)).toBe(1500);
  });
});

// ─── simSeriesN ───────────────────────────────────────────────────────────────

const makeTeam = (id: string, elo: number) => ({
  id,
  name: id,
  elo,
  currentWins: 0,
  remainingGames: 0,
  winProb: 0.5,
});

describe("simSeriesN", () => {
  it("best-of-3: winner reaches exactly 2 wins", () => {
    const a = makeTeam("A", 1600);
    const b = makeTeam("B", 1400);
    for (let i = 0; i < 100; i++) {
      const { winner, loser } = simSeriesN(a, b, 2);
      expect(winner === a || winner === b).toBe(true);
      expect(loser === a || loser === b).toBe(true);
      expect(winner).not.toBe(loser);
    }
  });

  it("best-of-5: winner and loser are always different teams", () => {
    const a = makeTeam("A", 1500);
    const b = makeTeam("B", 1500);
    for (let i = 0; i < 100; i++) {
      const { winner, loser } = simSeriesN(a, b, 3);
      expect(winner).not.toBe(loser);
    }
  });

  it("best-of-7: returns the input team objects (referential identity)", () => {
    const a = makeTeam("TeamA", 1550);
    const b = makeTeam("TeamB", 1450);
    const { winner, loser } = simSeriesN(a, b, 4);
    expect(winner === a || winner === b).toBe(true);
    expect(loser === a || loser === b).toBe(true);
  });

  it("heavily favored team wins most best-of-3 series", () => {
    const strong = makeTeam("Strong", 1800);
    const weak   = makeTeam("Weak",   1200);
    let strongWins = 0;
    const N = 1000;
    for (let i = 0; i < N; i++) {
      if (simSeriesN(strong, weak, 2).winner === strong) strongWins++;
    }
    // P(game) ≈ 0.994, P(series) should be > 0.99
    expect(strongWins / N).toBeGreaterThan(0.97);
  });

  it("even matchup produces roughly 50% win rate in a large sample", () => {
    const a = makeTeam("A", 1500);
    const b = makeTeam("B", 1500);
    let aWins = 0;
    const N = 2000;
    for (let i = 0; i < N; i++) {
      if (simSeriesN(a, b, 3).winner === a) aWins++;
    }
    // Should be close to 50% — allow ±5%
    expect(aWins / N).toBeGreaterThan(0.45);
    expect(aWins / N).toBeLessThan(0.55);
  });
});