202 lines
7.3 KiB
TypeScript
202 lines
7.3 KiB
TypeScript
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/**
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* EPL Season Standings Simulator
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*
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* Monte Carlo simulation of a Premier League table. Reads current actual
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* standings when present and simulates only the remaining season; if no current
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* standings exist, simulates a full 38-match season from 0 points.
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*
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* Results persist only placement probabilities (P1–P8) through the existing EV
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* pipeline. Simulated W/D/L/GF/GA/GD rows are internal and discarded.
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*/
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import { database } from "~/database/context";
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import { eq } from "drizzle-orm";
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import * as schema from "~/database/schema";
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import type { Simulator, SimulationResult } from "./types";
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import { getRegularSeasonStandings } from "~/models/regular-season-standings";
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import { convertFuturesToElo, eloWinProbabilityWithParity } from "~/services/probability-engine";
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import { normalizeSimulationResultColumns } from "./simulation-probabilities";
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import { simulateEloSoccerMatch, simulateSimpleSoccerGoals } from "./soccer-helpers";
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const NUM_SIMULATIONS = 10_000;
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const EPL_REGULAR_SEASON_GAMES = 38;
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const AVERAGE_OPPONENT_ELO = 1500;
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const PARITY_FACTOR = 400;
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const BASE_DRAW_RATE = 0.26;
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const DRAW_DECAY = 0.002;
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interface TeamEntry {
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id: string;
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elo: number;
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currentPoints: number;
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currentGoalsFor: number;
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currentGoalsAgainst: number;
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currentGoalDifference: number;
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remainingGames: number;
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}
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interface SimulatedTableRow {
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team: TeamEntry;
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points: number;
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goalsFor: number;
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goalsAgainst: number;
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goalDifference: number;
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tiebreaker: number;
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}
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/** EPL single-match win probability using the sport-specific parity factor. */
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export function eplWinProbability(eloA: number, eloB: number): number {
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return eloWinProbabilityWithParity(eloA, eloB, PARITY_FACTOR);
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}
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/** Simulate an EPL match result for team A vs team B. Exported for tests. */
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export function simEplMatch(eloA: number, eloB: number): "win" | "draw" | "loss" {
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return simulateEloSoccerMatch(eloA, eloB, {
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baseDrawRate: BASE_DRAW_RATE,
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drawDecay: DRAW_DECAY,
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parityFactor: PARITY_FACTOR,
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});
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}
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export class EPLSimulator implements Simulator {
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async simulate(sportsSeasonId: string): Promise<SimulationResult[]> {
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const db = database();
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const [participantRows, evRows, standings] = await Promise.all([
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db
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.select({ id: schema.seasonParticipants.id, name: schema.seasonParticipants.name })
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.from(schema.seasonParticipants)
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.where(eq(schema.seasonParticipants.sportsSeasonId, sportsSeasonId)),
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db
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.select({
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participantId: schema.seasonParticipantExpectedValues.participantId,
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sourceElo: schema.seasonParticipantExpectedValues.sourceElo,
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sourceOdds: schema.seasonParticipantExpectedValues.sourceOdds,
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})
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.from(schema.seasonParticipantExpectedValues)
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.where(eq(schema.seasonParticipantExpectedValues.sportsSeasonId, sportsSeasonId)),
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getRegularSeasonStandings(sportsSeasonId),
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]);
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if (participantRows.length === 0) {
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throw new Error(
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`No participants found for sports season ${sportsSeasonId}. Add all 20 EPL clubs before running simulation.`
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);
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}
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if (participantRows.length < 8) {
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throw new Error(
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`EPL simulation requires at least 8 participants to fill top-eight probabilities (got ${participantRows.length}).`
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);
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}
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const dbEloMap = new Map<string, number>();
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for (const row of evRows) {
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if (row.sourceElo !== null && row.sourceElo !== undefined) {
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dbEloMap.set(row.participantId, row.sourceElo);
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}
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}
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if (dbEloMap.size === 0) {
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const oddsInput = evRows
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.filter((row) => row.sourceOdds !== null && row.sourceOdds !== undefined)
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.map((row) => ({ participantId: row.participantId, odds: row.sourceOdds as number }));
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const converted = convertFuturesToElo(oddsInput);
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for (const [participantId, elo] of converted) dbEloMap.set(participantId, elo);
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}
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const missingElo = participantRows.filter((row) => !dbEloMap.has(row.id));
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if (missingElo.length > 0) {
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throw new Error(
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`Missing Elo/projected points for ${missingElo.length} EPL participants: ${missingElo.map((p) => p.name).join(", ")}. ` +
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`Enter Elo ratings or projected points via Admin → Elo Ratings before simulating.`
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);
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}
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const standingsMap = new Map(standings.map((standing) => [standing.participantId, standing]));
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const participantIds = participantRows.map((row) => row.id);
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const teams: TeamEntry[] = participantRows.map((row) => {
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const standing = standingsMap.get(row.id);
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const wins = standing?.wins ?? 0;
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const draws = standing?.ties ?? 0;
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const losses = standing?.losses ?? 0;
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const gamesPlayed = standing?.gamesPlayed ?? wins + draws + losses;
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const goalsFor = standing?.goalsFor ?? 0;
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const goalsAgainst = standing?.goalsAgainst ?? 0;
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const goalDifference = standing?.goalDifference ?? goalsFor - goalsAgainst;
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return {
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id: row.id,
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elo: dbEloMap.get(row.id) as number,
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currentPoints: standing?.tablePoints ?? wins * 3 + draws,
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currentGoalsFor: goalsFor,
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currentGoalsAgainst: goalsAgainst,
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currentGoalDifference: goalDifference,
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remainingGames: Math.max(0, EPL_REGULAR_SEASON_GAMES - gamesPlayed),
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};
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});
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const rankCounts = new Map<string, number[]>(
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participantIds.map((id) => [id, Array.from({ length: 8 }, () => 0)])
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);
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for (let sim = 0; sim < NUM_SIMULATIONS; sim++) {
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const tableRows: SimulatedTableRow[] = teams.map((team) => ({
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team,
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points: team.currentPoints,
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goalsFor: team.currentGoalsFor,
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goalsAgainst: team.currentGoalsAgainst,
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goalDifference: team.currentGoalDifference,
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tiebreaker: Math.random(),
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}));
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for (const row of tableRows) {
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for (let game = 0; game < row.team.remainingGames; game++) {
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const result = simEplMatch(row.team.elo, AVERAGE_OPPONENT_ELO);
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const goals = simulateSimpleSoccerGoals(result);
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row.goalsFor += goals.gf;
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row.goalsAgainst += goals.ga;
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row.goalDifference = row.goalsFor - row.goalsAgainst;
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if (result === "win") row.points += 3;
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else if (result === "draw") row.points += 1;
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}
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}
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const finalTable = tableRows.toSorted((a, b) =>
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b.points - a.points ||
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b.goalDifference - a.goalDifference ||
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b.goalsFor - a.goalsFor ||
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b.tiebreaker - a.tiebreaker
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);
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for (let rank = 0; rank < Math.min(8, finalTable.length); rank++) {
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const counts = rankCounts.get(finalTable[rank].team.id);
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if (counts) counts[rank]++;
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}
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}
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const results: SimulationResult[] = participantIds.map((participantId) => {
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const counts = rankCounts.get(participantId) ?? Array.from({ length: 8 }, () => 0);
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return {
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participantId,
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probabilities: {
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probFirst: counts[0] / NUM_SIMULATIONS,
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probSecond: counts[1] / NUM_SIMULATIONS,
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probThird: counts[2] / NUM_SIMULATIONS,
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probFourth: counts[3] / NUM_SIMULATIONS,
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probFifth: counts[4] / NUM_SIMULATIONS,
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probSixth: counts[5] / NUM_SIMULATIONS,
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probSeventh: counts[6] / NUM_SIMULATIONS,
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probEighth: counts[7] / NUM_SIMULATIONS,
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},
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source: "epl_standings_monte_carlo",
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};
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});
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normalizeSimulationResultColumns(results);
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return results;
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}
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}
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