How Monte Carlo Simulation Turns Match Predictions Into Tournament Win Probabilities

A technical explainer published on DEV Community outlines how to use Monte Carlo simulation to estimate a team's probability of winning a tournament, starting from a single-match prediction model. The core problem is that hand-multiplying win probabilities breaks down in bracket tournaments because future opponents are unknown and depend on other uncertain results. Monte Carlo simulation sidesteps this by repeatedly playing out the entire tournament thousands of times using a match-level model, such as a Poisson goals estimator, and tallying how often each team wins. Running tens of thousands of simulations allows the counts to converge into reliable tournament-level probabilities without manually enumerating every possible bracket path. The article also covers how many simulation runs are needed, how to attach confidence intervals to results, and where the method can produce misleading outputs.