[garion888]

This is the first time I have posted in this forum so what's up everyone [img]/images/graemlins/smile.gif[/img]

I have been trying to come up with a luck factor to determine how bad one might run with respect to raw receipt of hands.

The question comes up when you have a small sample size of whether you are getting cold decked or if you are just playing badly. I want to determine a way of understanding the amount of cold decking going on to determine what might be the cause of a bad or breakeven run. This could also be used to understand if you are running exceptionally well during a short stretch of hands.

For my test case I have been using a 4958 hand stretch of my PT database in which I held 288 pocket pairs. I wanted to determine the luck factor associated with flopping sets. During this stretch of hands I flopped 28 sets. I should have flopped 35-36 sets during this sample(someone correct me if i'm wrong).

So I took the sum of the binomial distribution between n=0 and n=28 for N=288,p=1/8. I took the same sum between n=0 and n=36. The former result was .087 and the latter result was .54. Dividing the former by the latter and you get the luck factor L = .16.

If the luck factor is less than 1 you have been running bad in terms of raw receipt of said hand(a set on the flop in this case). If its greater than 1 then you are running well.

I think I need a little help in understanding the metric a little more. How unlucky is a .16 vs a .17. And is the metric linear. Is the difference in luck between a .16 and a .17 the same between a .56 and a .57?

Thanks
-j