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RTP & Simulation Validation

To validate the shipped game math, a Monte Carlo harness ran the production engines verbatim (lifted from serverless/entropy.js, serverless/crash.js, serverless/lootbox.js) — 10,000 bets per Entropy entry, 0.01 ETH bets, a virtually funded 50 ETH treasury per game. Source: scripts/sim-entropy-rtp.cjs.

Results — 10,000 bets each

No treasury busted at 50 ETH with 0.01 bets. Worst drawdown was −31% (Limbo 100× — the swingiest entry).

Aggregate house view (130k bets)

RTP progression insights

  • Low-variance games converge fast and cleanly. Mines 3 walks 97.66% → 99.00% in a near-straight line; Crash 2× locks onto ~95.5% by bet 3,000. Exactly the 99%/96% theory.
  • High-variance games swing hard in finite samples. Limbo 100× sat at 50% RTP for 2,000 bets (zero 100× hits — pure tail luck) before clawing to 89%. Keno 10 opened at 118.5% (an early top-tier hit) then drifted to 91%.
  • Tails need volume. Expect ~100k–1M bets for the extreme-multiplier entries to converge inside ±2%. This is expected statistics, not a math problem — the engines are exactly on their designed edges.
  • The floor2 rounding in the engines shaves a hair below theory on small-multiplier configs (visible on Mines).

What this means operationally

Re-run it yourself:
Next: API Reference.
Last modified on October 6, 2026