bet-mcp

import { config } from "../config.js"; import { FairOddsPayload, MatchSnapshot, SelectionKey } from "../types.js"; import { clampProbability, poissonProbability } from "../utils/math.js"; const MAX_GOALS = 8; export const computeFairOddsFromSnapshot = (snapshot: MatchSnapshot): FairOddsPayload => { const lambdaHome = deriveLambda( snapshot.home.avgGoalsFor, snapshot.away.avgGoalsAgainst, config.modeling.homeAdvantage, ); const lambdaAway = deriveLambda(snapshot.away.avgGoalsFor, snapshot.home.avgGoalsAgainst, 1); const { homeWin, awayWin, draw, over25, bttsYes } = integrateDistributions(lambdaHome, lambdaAway); const probs = { HOME: clampProbability(homeWin), DRAW: clampProbability(draw), AWAY: clampProbability(awayWin), OVER_2_5: clampProbability(over25), UNDER_2_5: clampProbability(1 - over25), BTTS_YES: clampProbability(bttsYes), BTTS_NO: clampProbability(1 - bttsYes), } satisfies Record<SelectionKey, number>; const fairOdds = Object.fromEntries( Object.entries(probs).map(([key, value]) => [key, Number((1 / value).toFixed(3))]), ) as Record<SelectionKey, number>; return { matchId: snapshot.match.matchId, lambdaHome: Number(lambdaHome.toFixed(3)), lambdaAway: Number(lambdaAway.toFixed(3)), probabilities: probs, fairOdds, }; }; const deriveLambda = ( goalsFor = 1.2, goalsAgainst = 1.2, adjustment = 1, ): number => { const baseline = (goalsFor + goalsAgainst) / 2; return Math.max(0.4, baseline * adjustment); }; const integrateDistributions = (lambdaHome: number, lambdaAway: number) => { const homeDist = buildDistribution(lambdaHome); const awayDist = buildDistribution(lambdaAway); let homeWin = 0; let draw = 0; let awayWin = 0; let over25 = 0; let bttsYes = 0; for (let h = 0; h <= MAX_GOALS; h += 1) { for (let a = 0; a <= MAX_GOALS; a += 1) { const prob = homeDist[h] * awayDist[a]; if (h > a) homeWin += prob; else if (a > h) awayWin += prob; else draw += prob; if (h + a >= 3) over25 += prob; if (h > 0 && a > 0) bttsYes += prob; } } const total = homeWin + awayWin + draw; if (total > 0) { homeWin /= total; awayWin /= total; draw /= total; } return { homeWin, awayWin, draw, over25, bttsYes }; }; const buildDistribution = (lambda: number): number[] => { const dist: number[] = []; for (let goals = 0; goals <= MAX_GOALS; goals += 1) { dist[goals] = poissonProbability(lambda, goals); } return dist; };