You have a 43% chance of winning each hand with a payoff of 1.31 to 1.

Edge of 67 bps, SD of 1.14. Plenty accurate for my calculations, which are usually figuring how much bankroll I need for a certain level/length of play

True, but my point was, six times slower could still be fast enough. Based on how fast my Java sim ran on my old computer and my new computer, and how fast my LiveCode sim ran on my old computer, I estimate that LiveCode could sim 1.5 million rounds per minute. That would be plenty for lots of applications. I suspect Javascript and Python would be even faster.Quote:BleedingChipsSlowlyIn general, based on the study, what takes 10 hours to run for C will take 17 hours for Java and 56 hours for Python.

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That's more like an estimation than a simulation. A true simulation lets you change parameters to test things. For example, my blackjack sim can be modified to do things like find the penalty for strategy deviations, or the efficacy of card-counting systems.Quote:Ace2Another very easy way to simulate blackjack:

You have a 43% chance of winning each hand with a payoff of 1.31 to 1.

Edge of 67 bps, SD of 1.14

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Quote:Ace2Another very easy way to simulate blackjack:

You have a 43% chance of winning each hand with a payoff of 1.31 to 1.

Edge of 67 bps, SD of 1.14. Plenty accurate for my calculations, which are usually figuring how much bankroll I need for a certain level/length of play

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I’ve read this a few times but still don’t understand what you are talking about.

What is this 1.31 to 1 payoff? It looks like you are talking about an expected win amount of 1.31 for each 1-unit-bet winning hand, but this number doesn’t sound right.

A simulation of play would provide the information used in this calculation. As MichaelBluejay pointed out, the calculation is an application of the simulation information in the context of this thread.

Quote:BleedingChipsSlowlyThe expected win is 1.31 per 1 wagered for 43% of hands played. So (1.31 + 1) * 0.43 = 0.9933 expected value (EV) for a wager if one, a house edge of 0.67%.

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I am confused here, but we need both the win rate and the loss rate to calculate the house edge. The win rate is 43%, the loss rate is 50%, and the tie rate is 7%. Let us set the expected win amount of each winning hand as x, then we have

50%*1 - 43%*x = 0.67%.

This gives x=1.15.

He loops through every possible combination of cards (once), accumulating statistical outcome information.

Absent a specific mention of pushes, I went with the theory that pushes are classified as a win. The resulting 0.67% house edge is in line with 6:5 red chip tables and stadium games. I could be wrong. Perhaps Ace2 will clarify.Quote:acesideQuote:BleedingChipsSlowlyThe expected win is 1.31 per 1 wagered for 43% of hands played. So (1.31 + 1) * 0.43 = 0.9933 expected value (EV) for a wager if one, a house edge of 0.67%.

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I am confused here, but we need both the win rate and the loss rate to calculate the house edge. The win rate is 43%, the loss rate is 50%, and the tie rate is 7%. Let us set the expected win amount of each winning hand as x, then we have

50%*1 - 43%*x = 0.67%.

This gives x=1.15.

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Such a bet is statistically congruent to blackjack. It will give you essentially the same results, variance and RoR as blackjack as long as your sample size is above about 100 hands. But it’s much easier to do calculations for this simple bet since there is no splitting, doubling, pushes, blackjacks or surrendering.

It’s pretty easy to manually calculate the effect of many strategy deviations and then modify the 0.43 and 1.31 as needed. But that combination, giving and edge/SD of 0.67% / 1.14, is pretty accurate for most 3:2 games.

For strategy deviations, I always assume infinite deck which makes the calculations much easier. I’ve found that as long as more than two decks are being used, the infinite deck answer is within a couple basis points of the exact answer

Yep, just like craps. All you gotta do is turn off bets right before a 7 is rolledQuote:ChumpChangeSo you just have to bet on the 43% of hands that actually win something. The other 57% can be skipped through mnemonic intrigue.

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