The theoretical return is 98.7649%. When I run 1 billion hands, the average return is 98.7623%. This simulation is broken down as previously mentioned. The standard deviation of repayment is 0.9475% and the 95% confidence interval is 1.8571%. This means that if I run a 10,000 hand simulation, that 95% of the time, I should find that the returns to be between 96.9052% and 100.6193%. This is for games with relatively low volatility and more than 10,000 hands.
I recently ran. What I find interesting is that over 10,000 baccarat hands, a player should expect to win several “significant” times. The numbers presented so far don’t really tell us how often. So I dug through the statistics and found that 9.4% of the time, players will win more than 10,000 hands visit KudaQQ. That’s plenty of hands for a player to still find himself on the winning side of the ledger for a game with a moderate home edge.
Of course, the banker bet is even better for the player and we found that he would still win 12.73% of the time after 10,000 hands. The volatility of the stakes is very similar. The biggest difference is that banker bets have a house edge of about 0.2% smaller. Imagine what numbers we might find if we did something similar for Blackjack with a house edge of roughly half the banker’s bet.
Unsurprisingly, the lower the return, the less likely you are to see a player still winning after 10,000 hands. If I look at the data for a sidebet with a 90% return, I’m likely to find zero or almost zero times the player has still won. It’s also not surprising, as the sample size increases, the number of sessions a player will still win will quickly decrease as well.
When I move 100,000 hands, I will probably find that the player is unlikely to win at the end of one of them. But, it’s nice to know that in the not too short span of time, your little one still has a chance.
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