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Results:
for 100 hand spans using 13400 hands the confidence interval (usually you use 90% or 95%, that means in 90% you will be below this win rate over 100 hands) is:
90%: 103.65bb/100
95%: 124.07bb/100
99%: 164.15bb/100
99.999%: 283.99bb/100
99.99999999999%: 480.77bb/100
or 1:10000000000000 or 1:10E14

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Interesting analysys. Good work. We need more of this.

If i interpret your results correctly, under the assumptions your model is correct, if you have 100.000 streaks of 100 hands each, one of those will show a win rate of 284bb/100 just by chance? How many hands are there in ppls PT-databases (which would be the population) and what is the probability that every once in a while we will find a maniac with those winnings without cheating?

And what if you increase the standard deviation a little? I mean, this kind of maniac could have a SD of 100 right? That would make it even more probable that such good streak could occur right?

your model also assumes that winnings are normally distributed. Do you think this is a good assumption and in what way do you think violations th normality would affect the estimated probabilities?


EDIT: I just saw that the had a SD of 270ptbb/100 and that it was 190 hands. That will give completely different estimates. It would be very interesting if you could present a new analysis with those paramters.

My guessing is that you will find a very high probabbility that such streak would occur in ppls PT databases, more than once.