Monte Carlo Simulator
Simulate thousands of pack openings to see the full range of possible outcomes. Unlike a single EV number, Monte Carlo shows you the probability distribution — how likely you are to profit, lose, or hit big.
Simulations per run
True success rate
Realistic range
How It Works
Four concepts that make Monte Carlo more honest than a single EV number.
Monte Carlo simulation opens virtual packs thousands of times, each pull seeded by real pull rates and card-price distributions. Instead of one average outcome, you see every realistic one.
Standard deviationStd Dev controls how much card prices vary inside a tier. A Hyper Rare tier with $80 avg and $50 std dev means some cards are worth ~$30 and others ~$130+.
Profit probability the share of simulated openings that beat the product cost after marketplace fees. This is the number that matters — EV can be positive while profit probability is below 50% if a handful of lucky pulls skew the average upward.
90% confidence interval the realistic range your outcome will land in 9 times out of 10. The outer 10% are extreme outliers — both blessed and cursed.
When to trust the numbers
Sets with solid price coverage across every rarity tier. The more cards we have market data for, the tighter the confidence intervals become.
When to squint
Newly released sets, obscure rarities, or single-pull chase cards dominating a tier. One $500 outlier can warp the mean — always cross-check profit probability, not just EV.