Betting variance simulator
Run Monte Carlo simulations to understand how variance affects your betting results. See risk of ruin, expected drawdowns, and profit distribution across thousands of scenarios.
= 20.00 per bet
Configure your parameters and click Simulate to run the Monte Carlo simulation
5000 simulations x 1000 bets each
See how your actual results compare to expected variance in Trackbet's analytics dashboard.
Sign up freeWhat is variance in betting?
Variance is the natural randomness in betting results that causes your actual profit to deviate from your expected profit, especially over short sample sizes. Even with a genuine 3% edge, it is entirely normal to experience losing months — variance can mask your edge for hundreds or even thousands of bets. Understanding variance is essential for managing expectations and bankroll effectively.
Understanding Monte Carlo simulation
A Monte Carlo simulation generates thousands of possible outcomes by simulating random bet sequences using your edge, odds, and staking method. Each simulation represents one possible future — and together, they paint a complete picture of every possible path your bankroll could take. This helps you understand the best case, worst case, and everything in between.
Risk of ruin explained
Risk of ruin is the probability that your bankroll will be completely depleted. Even with positive expected value, aggressive staking or insufficient bankroll can lead to ruin due to natural variance. The Kelly criterion mathematically minimises risk of ruin while maximising growth — but most bettors use fractional Kelly to further reduce this risk.
Flat staking vs Kelly staking
Flat staking bets a fixed percentage of your initial bankroll on every bet. Simple and predictable, but doesn't adapt to your bankroll growth or shrinkage.
Kelly staking adjusts your stake based on your current bankroll and edge. When your bankroll grows, you bet more; when it shrinks, you bet less. This proportional approach protects against ruin while capitalising on winning streaks. Use this simulator to visually compare both approaches.
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