Monte Carlo simulations are a powerful method for generating forecasts—predicted scenarios with associated probabilities. These simulations are widely used across various fields, from estimating constants like π and e to predicting weather patterns and modeling fission energy production. In fact, the Monte Carlo method was originally developed by John von Neumann and his colleagues at Los Alamos during the Manhattan Project to simulate atomic collisions in fission reactions.

A Monte Carlo simulation works by assigning multiple values to a single variable, generating multiple results, and then averaging them to estimate likely outcomes. For example, if we wanted to analyze land draw rates for different deck compositions, we could simulate thousands of games and weight the results to determine the most probable outcome. Similarly, we could estimate the likelihood of drawing into a combo with n number of key cards.