Monte Carlo Sim

MLB Monte Carlo game simulations

Every game simulated thousands of times to produce win probabilities and run distributions for moneylines, run lines and totals, with the gap between the simulated price and the market price shown for each.

Why simulate instead of projecting a score

A single projected score throws away the thing you actually need. Baseball outcomes are a distribution, and two games with the same projected total of 8.5 runs can have very different chances of going over, depending on how the runs are likely to be distributed between the teams and the innings.

Simulation keeps the shape. Running a game many times produces the full range of outcomes, which is what lets you price a run line properly. Winning by exactly one run is a common baseball result, so the difference between a moneyline and a run line is a question about distribution rather than about who is better.

It also handles the interactions that a spreadsheet cannot. Bullpen availability, park, weather and lineup order all affect each other, and the only practical way to see the combined effect on a run distribution is to play the game out repeatedly.

Reading an edge without overreacting to it

The number worth acting on is the difference between the simulated probability and the price implied by the market. A small edge is inside the model's own error bar and is not a bet. A large edge usually means the model is missing something the market knows, most often a lineup or an injury, so check before assuming you have found something.

The market is a strong baseline. Treat a simulation as a second opinion that identifies where to look more closely, rather than as a number that overrides a price set by everyone betting into it.

Frequently asked questions