Crash Gambling EV Calculator

How to read the output

For a "1/x" distributed crash game (the most common model), the probability of reaching multiplier x before crashing is (1 - edge) / x. So at 2× target with 1% edge, your win probability is ~49.5%. At 10× target, it\'s ~9.9%. At 100×, ~0.99%.

Expected payout per round (if you cash out at target x): x × win_prob × bet = (1 - edge) × bet. Notice the target multiplier cancels out — your expected loss per round is always edge × bet, regardless of which multiplier you choose. The only thing the target changes is variance.

What target should you pick?

Math says it doesn\'t matter (long run, you lose edge × total_wagered regardless of target). Variance says it matters a lot:

• Low targets (1.2× - 2×): Win often, win small. Smooth bankroll curve. Less excitement.
• Mid targets (5× - 10×): Balanced variance. Most popular range.
• High targets (50× - 100×): Rare massive wins, long losing streaks between them. Bankroll death without discipline.

Bankroll survival math

Even at break-even EV (zero edge), a finite bankroll has nonzero probability of going to zero on the wrong streak. With house edge, the expectation drifts negative, accelerating ruin. Kelly criterion suggests betting (edge × win_chance) / multiplier of bankroll per round — though for crash gambling Kelly is usually overkill; conservative players use 1-2% of bankroll per bet regardless of strategy.

Worked example: 100 rounds at 2× target, $10 bet, 1% edge

• Win probability per round: 49.5%
• Expected wins: 49.5 rounds → 49.5 × $10 × 2 = $990 returned
• Expected losses: 50.5 rounds → 50.5 × $10 = $505 lost
• Total wagered: $1,000
• Net expected: $990 - $505 - $0 (no extra fees) = $485 returned vs $500 wagered = -$15
• That -$15 is exactly 1% × $1,500 = the house edge × total bet volume

The variance around that -$15 is enormous. Many 100-round sessions will be profitable; many will be much worse than -$15. The math only converges over thousands of rounds.

Common questions