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Message: [QUOTE="vinnie, post: 2127213, member: 95995"] There is a mathematical solution to your question, but it's not simple. It involves using statistics. Basically, you're asking how large of a sample size do we need, given a certain probability and standard deviation, before we can be reasonably certain that our results will be reasonably close to the expectation? The answer to that question is complicated and relies on what you mean by being reasonably close. When we're dealing with something that has high amounts of variance (flopping a set, for example) we need an even larger sample size than when dealing with something with low variance (flipping a coin). In my own databases, I have thousands of hands. Take one site, I had 4,116 pairs where I saw a flop. I would expect to flop a set or better (quads / full house) 484 times. I happened to make that 487 times. So I was slightly above expectation. The standard deviation of this sample is about 20. So I am only off by 6% of the expectation. That's not bad. Over this sample, 33% of the time I can expect to be more than 20 hands above or below the 484 flopped sets. Anyway, the short answer to your question is that you need LOTS of hands. I would be comfortable with any sample size greater than 100 hands. At that point, you're well into the outer edges of probability. Pairs seeing a flop in a row with no sets. 25: Probability 3.39% (339 times in 10,000 opportunities) 50: Probability 0.5% (50 times in 10,000 opportunities) 75: Probability 0.08% (8 times in 10,000 opportunities) 100: Probability 0.03% (3 times in 10,000 opportunities) As you can see, increasing the sample size can have dramatic impacts on the probability. Of course, 100 hands in a row without hitting a set would be pretty impressive. [/QUOTE]

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