Betting Tools

Monte Carlo Simulator

Simulate bankroll trajectories from expected ROI and variance to visualize risk, drawdowns, and outcome dispersion.

ROI-driven model
ROI is the starting point. In this fixed-odds model, average odds, win probability, and variance stay linked to that ROI, so changing one of them updates the others when the numbers still make sense together.

Assumptions: starting bankroll 1000 units and a constant stake sized as a percentage of the starting bankroll.

Input ranges: ROI -100% to 100%, variance 0% to 500%, bankroll per bet 0.01% to 100%, bets 1 to 10000, simulations 10 to 5000, average odds 1.01 to 100, win probability 0.01% to 99.99%.

The simulator uses a fixed-odds betting model, with ROI treated as the base expected return per bet.

Average odds and win probability determine each other through ROI, while variance can be used to infer the missing side under the same model.

Bankroll trajectory
One selected profit trajectory with the full min-to-max simulation range and a visible zero-profit line.
Zero profit line
Selected series
Median
Max downstreak
6 bets
6.00u • 6.00%
Max drawdown
20.60u
20.60%
Max upstreak
12 bets
9.60u • 9.60%
Win rate
57.40%
Final profit
16.60u
16.60%
Realized ROI
3.32%

What this Monte Carlo simulator does

This tool simulates many possible betting paths from your expected ROI, odds, win probability, variance, stake size, and sample length. Instead of showing only one expected outcome, it shows a range of possible results so you can judge volatility, downside, and how rough the ride can be even with a profitable edge.

It is useful when you want to sanity-check bankroll risk, compare short-term variance against long-term expectation, and understand what normal losing streaks or drawdowns might look like for your strategy. The chart shows one selected trajectory against the full simulation envelope, while the stats summarize streaks, drawdown, win rate, final profit, and realized ROI for that selected path.

Use it as a decision-support tool, not as a prediction engine. The output is only as good as the assumptions you enter, so realistic ROI, win probability, and stake sizing matter much more than the number of simulations.