brackt/app/services/simulations/__tests__/input-policy.test.ts

import { describe, expect, it } from "vitest";
import { resolveRatings, resolveSourceElos } from "../input-policy";
import type { SimulatorManifestProfile } from "../manifest";

const profile = {
  derivableInputs: { sourceElo: ["projectedWins", "sourceOdds"] },
} as Pick<SimulatorManifestProfile, "derivableInputs">;

const tablePointsProfile = {
  derivableInputs: { sourceElo: ["projectedTablePoints"] },
} as Pick<SimulatorManifestProfile, "derivableInputs">;

describe("simulator input policy", () => {
  it("keeps direct Elo ahead of derived values", () => {
    const resolved = resolveSourceElos(
      [{ participantId: "team-1", sourceElo: 1600, rating: null, sourceOdds: 2000, projectedWins: 20, projectedTablePoints: null }],
      profile,
      { seasonGames: 82 }
    );

    expect(resolved.get("team-1")).toMatchObject({ sourceElo: 1600, method: "direct" });
  });

  it("derives Elo from projected wins when Elo is missing", () => {
    const resolved = resolveSourceElos(
      [{ participantId: "team-1", sourceElo: null, rating: null, sourceOdds: null, projectedWins: 60, projectedTablePoints: null }],
      profile,
      { seasonGames: 82, parityFactor: 400 }
    );

    expect(resolved.get("team-1")?.method).toBe("projectedWins");
    expect(resolved.get("team-1")?.sourceElo).toBeGreaterThan(1500);
  });

  it("uses parityFactor as the projected table points to Elo spread", () => {
    const input = {
      participantId: "team-1",
      sourceElo: null,
      rating: null,
      sourceOdds: null,
      projectedWins: null,
      projectedTablePoints: 76,
    };

    const compressed = resolveSourceElos([input], tablePointsProfile, {
      seasonGames: 38,
      parityFactor: 250,
    });
    const wider = resolveSourceElos([input], tablePointsProfile, {
      seasonGames: 38,
      parityFactor: 1000,
    });

    expect(compressed.get("team-1")?.sourceElo).toBeLessThan(wider.get("team-1")?.sourceElo ?? 0);
  });

  it("blocks missing Elo unless a fallback strategy is configured", () => {
    const inputs = [{ participantId: "team-1", sourceElo: null, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null }];

    expect(resolveSourceElos(inputs, profile, {}).has("team-1")).toBe(false);
    expect(resolveSourceElos(inputs, profile, {
      inputPolicy: { missingEloStrategy: "fallbackElo", fallbackElo: 1375 },
    }).get("team-1")).toMatchObject({ sourceElo: 1375, method: "fallbackElo" });
  });

  it("supports worst-known-minus tail fallback", () => {
    const resolved = resolveSourceElos(
      [
        { participantId: "known-1", sourceElo: 1500, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
        { participantId: "known-2", sourceElo: 1430, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
        { participantId: "tail", sourceElo: null, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
      ],
      profile,
      { inputPolicy: { missingEloStrategy: "worstKnownMinus", fallbackEloDelta: 30 } }
    );

    expect(resolved.get("tail")).toMatchObject({ sourceElo: 1400, method: "worstKnownMinus" });
  });

  it("derives Elo from futures odds when no direct Elo is present", () => {
    const resolved = resolveSourceElos(
      [
        { participantId: "favorite", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
        { participantId: "longshot", sourceElo: null, rating: null, sourceOdds: 20000, projectedWins: null, projectedTablePoints: null },
      ],
      profile,
      {}
    );

    expect(resolved.get("favorite")?.method).toBe("sourceOdds");
    expect(resolved.get("longshot")?.method).toBe("sourceOdds");
    expect(resolved.get("favorite")?.sourceElo).toBeGreaterThan(resolved.get("longshot")?.sourceElo ?? Infinity);
  });

  it("ignores a lone sourceOdds participant rather than assigning a flat Elo", () => {
    const inputs = [
      { participantId: "only", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
    ];

    // Needs at least 2 odds to derive a spread; with block strategy it stays unresolved.
    expect(resolveSourceElos(inputs, profile, {}).has("only")).toBe(false);

    // With a fallback strategy it resolves via that method, not "sourceOdds".
    expect(
      resolveSourceElos(inputs, profile, {
        inputPolicy: { missingEloStrategy: "fallbackElo", fallbackElo: 1400 },
      }).get("only")
    ).toMatchObject({ sourceElo: 1400, method: "fallbackElo" });
  });

  it("derives Elo from odds once a prior direct Elo has been cleared", () => {
    // Regression: after entering futures odds the simulator inputs row keeps
    // sourceOdds but has its sourceElo nulled. The resolver must pick "sourceOdds",
    // not resurrect a "direct" Elo.
    const resolved = resolveSourceElos(
      [
        { participantId: "favorite", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
        { participantId: "longshot", sourceElo: null, rating: null, sourceOdds: 20000, projectedWins: null, projectedTablePoints: null },
      ],
      profile,
      {}
    );

    expect(resolved.get("favorite")?.method).toBe("sourceOdds");
    expect(resolved.get("longshot")?.method).toBe("sourceOdds");
  });

  it("derives ratings from futures odds when the profile allows it", () => {
    const resolved = resolveRatings(
      [
        { participantId: "favorite", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
        { participantId: "longshot", sourceElo: null, rating: null, sourceOdds: 20000, projectedWins: null, projectedTablePoints: null },
      ],
      { derivableInputs: { rating: ["sourceOdds"] } },
      { inputPolicy: { ratingMin: -10, ratingMax: 35 } }
    );

    expect(resolved.get("favorite")?.method).toBe("sourceOdds");
    expect(resolved.get("longshot")?.method).toBe("sourceOdds");
    expect(resolved.get("favorite")?.rating).toBeGreaterThan(resolved.get("longshot")?.rating ?? 999);
  });

  it("blocks missing ratings unless a rating fallback strategy is configured", () => {
    const inputs = [
      { participantId: "known", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
      { participantId: "longshot", sourceElo: null, rating: null, sourceOdds: 20000, projectedWins: null, projectedTablePoints: null },
      { participantId: "tail", sourceElo: null, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
    ];
    const ratingProfile = { derivableInputs: { rating: ["sourceOdds"] } } as Pick<SimulatorManifestProfile, "derivableInputs">;

    expect(resolveRatings(inputs, ratingProfile, {
      inputPolicy: { ratingMin: -10, ratingMax: 35 },
    }).has("tail")).toBe(false);

    expect(resolveRatings(inputs, ratingProfile, {
      inputPolicy: {
        missingRatingStrategy: "fallbackRating",
        fallbackRating: -4,
        ratingMin: -10,
        ratingMax: 35,
      },
    }).get("tail")).toMatchObject({ rating: -4, method: "fallbackRating" });
  });

  it("supports worst-known-minus rating fallback with clamping", () => {
    const resolved = resolveRatings(
      [
        { participantId: "favorite", sourceElo: null, rating: 30, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
        { participantId: "known-tail", sourceElo: null, rating: -8, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
        { participantId: "missing-tail", sourceElo: null, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
      ],
      { derivableInputs: { rating: ["sourceOdds"] } },
      {
        inputPolicy: {
          missingRatingStrategy: "worstKnownMinus",
          fallbackRatingDelta: 5,
          ratingMin: -10,
          ratingMax: 35,
        },
      }
    );

    expect(resolved.get("missing-tail")).toMatchObject({ rating: -10, method: "worstKnownMinus" });
  });

  it("uses NCAAW-style rating scale when deriving and falling back", () => {
    const resolved = resolveRatings(
      [
        { participantId: "favorite", sourceElo: null, rating: null, sourceOdds: 300, projectedWins: null, projectedTablePoints: null },
        { participantId: "longshot", sourceElo: null, rating: null, sourceOdds: 20000, projectedWins: null, projectedTablePoints: null },
        { participantId: "tail", sourceElo: null, rating: null, sourceOdds: null, projectedWins: null, projectedTablePoints: null },
      ],
      { derivableInputs: { rating: ["sourceOdds"] } },
      {
        inputPolicy: {
          missingRatingStrategy: "worstKnownMinus",
          fallbackRatingDelta: 0.05,
          ratingMin: 0.15,
          ratingMax: 0.99,
        },
      }
    );

    expect(resolved.get("favorite")?.rating).toBeLessThanOrEqual(0.99);
    expect(resolved.get("tail")).toMatchObject({ rating: 0.15, method: "worstKnownMinus" });
  });
});