[BillC]

The use of the normal distribution arises from the belief that bets (or an hour of play, or sets of 100 hands) are approximately independent. The net result of independent bets converges (with increasing number of trials) to a normal random variable. If you think the independence of bets or sets of bets does not approximately hold, it might be interesting to hear why.

The beauty of simple games of chance such as poker and blackjack, as opposed to say financial instruments, is that our assertion of approximate normality is much easier to justify (because of the ramdomness of the shuffle. please do not take this as bait).

That being said, it would be interesting to see data to suggest that (say for sets of 100 hands) results are or are not approximately normal or symmetric, i.e. that they are skewed. Anyone have data on this? I would be surprised to see any sinifigant skewing.

The normal/Brownian motion model is a continuous approximation of a discrete reality, and the speed of convergence to the idealized model can be hampered by skewing. In the case of skew, larger samples are needed for accurate predictions.

The poster above may be confusing positive EV with skewing in the sense that the distribution of results is asymmetric about the mean.