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How can two bets have the same edge but different volatility?
The edge is the average cost. Volatility is how the money comes back. On double-zero roulette:
| Bet | Pays | Chance of winning | House edge |
|---|---|---|---|
| Red or black | 1 to 1 | 18 in 38, about 47% | 5.26% |
| Single number | 35 to 1 | 1 in 38, about 2.6% | 5.26% |
Our own count from 38 pockets. Edge from Wizard of Odds.
What does volatility mean for slots?
A high-volatility slot pays rarely but can pay large amounts, and a low-volatility slot pays smaller amounts more often. Wizard of Odds gives Dead or Alive as an example of a high-volatility slot, with a 96.82% RTP and a top prize of 12,000 times the bet. Most slots do not publish a volatility figure, though some lobbies label games low, medium or high.
How does volatility affect your budget?
With the same budget, higher volatility usually means a session ends sooner. A 2007 simulation study at the University of Nevada, Las Vegas, held the house edge constant and found that games with a higher pay table standard deviation gave losing players fewer spins. The authors called a game's standard deviation "a crucial determinant" of a slot player's experience.
Which should you choose?
The right volatility depends on what you want from a session, not on which is better value. Volatility does not change the average cost, which is set by the RTP or house edge.
- Low volatility: more small wins, longer play on a fixed budget.
- High volatility: long dry spells, with a chance of a large win.
- Either way, check the RTP first. See how to find a slot's RTP.
What are the rules in your state?
Each state sets its own online casino rules. Pick a state to see its status, its regulator and the date we last checked it.
Read next: Payout rates
Sources
Checked November 5, 2026. Regulator rules were read through the sources listed, and they can change. How we research.
- Wizard of Odds: slots
- Wizard of Odds: house edge of casino games compared
- Wizard of Odds: roulette basics
- Lucas, Singh and Gewali: pay table standard deviation and pulls per losing player, UNLV Gaming Research & Review Journal (2007)
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