Part III: Business & Regulation · Gambling Mathematics & Probability

63. Monte Carlo Simulation

Risk Management

Monte Carlo simulation is a computational technique that uses repeated random sampling to model the probability of different outcomes in complex systems where analytical solutions are difficult or impossible. In casino game design, Monte Carlo simulations are used to verify theoretical RTP calculations, estimate confidence intervals, model bankroll requirements, and analyze game volatility. Gaming laboratories like GLI use Monte Carlo methods to validate game mathematics by simulating millions or billions of game rounds and comparing actual results to theoretical expectations. Casino operators use Monte Carlo analysis to determine appropriate float levels, set progressive jackpot seed amounts, and project revenue under various scenarios.

In practice

Monte Carlo methods are named after the Monte Carlo Casino in Monaco. The technique was developed during the Manhattan Project and is now fundamental to financial modeling, physics, and gaming mathematics. Modern casino game simulations often run billions of hands or spins to achieve statistical significance.

One entry from the Casino Industry Glossary — 1,157 terms written for surveillance, compliance and operations professionals rather than for players. Definitions describe industry usage; where a term carries a regulatory meaning, verify against the instrument that governs your jurisdiction.