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multiwayEquityIndependenceGap

Monte Carlo multiway equity vs the independence approximation 1 − Π(1 − huEquity_j) — reports exact estimate, approximation, and gap.

multiwayEquityIndependenceGap(heroHoleCards: CardInput, boardCards: CardInput, numSimulations: number, seed: number, villains: number): MultiwayIndependenceGapResult

See Packed card input.

Import​

const poker = require('poker-calculations');

ESM (Node):

import { createRequire } from 'module';
const require = createRequire(import.meta.url);
const poker = require('poker-calculations');

When to use​

You want to measure how much treating villains as independent mis-estimates multiway equity — for study, model validation, or deciding when to use full multiway simulation.

How to use​

const poker = require('poker-calculations');

const { exact, independentApprox, gap, villains } = poker.multiwayEquityIndependenceGap(
  ['Ah', 'Kh'],
  ['Qh', 'Jh', '2c'],
  50_000,
  42,
  2,
);

console.log({ exact, independentApprox, gap, villains });

Increase numSimulations for stabler estimates. Both values are Monte Carlo — not exact enumeration.

Return type​

MultiwayIndependenceGapResult.

See also​

simulateHandOutcome · simulateEquityVsRange · Multiway