[8Mile]

You're not going to like the answer.

A 95% confidence interval (95% CI) for the win rate per hand (Xbar) is given by Xbar ± 1.96 * S / sqrt(n), where S is the standard deviation per hand and n is the number of hands. The half-width of this interval, that is, 1.96 * S / sqrt(n) is a conventional measure of the precision of X-bar, in this case, the estimate of the win rate per hand. So, to determine how big n has to be give us a desired level of precision for our win rate, we can set the above expression equal to the desired level of precision, and solve for n. Let's say we want to estimate our win rate per 100 hands to ± 0.5 BB/100. This is equivalent to measuring our win rate per hand to ± 0.005. So, our equation for n becomes

n = (1.96 * S / 0.005)^2.

A reasonable value for S is 1.5. Solving for n, we find we need about 346,000 hands to estimate our win rate per 100 hands to within 1/2 a BB. Like I said, you won't like the answer.

If you are satisfied with worse precision, the following table might be helpful. The first column is the desired precision (BB/100), the second column is the number of hands required.

0.5 ... 345744
1 ..... 86436
1.5 ... 38416
2 ..... 21609