Monte Carlo Match Simulation: Running Thousands of Virtual Football Matches

How Monte Carlo Simulation Works

The simulation then runs 10,000 or more iterations of the match, each with randomly sampled values from these distributions. The aggregate results produce stable probability estimates for match outcomes.

Advantages Over Point Estimates

Simple prediction models produce point estimates (e.g., Team A scores 1.8 goals). This is essential for accurate odds calculation and for markets like correct score, where tail probabilities matter significantly.

Incorporating Uncertainty

A key strength of Monte Carlo methods is their natural handling of uncertainty.