[DrVanNostrin]

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I believe (I may be mistaken) that the Sklansky bucks calculations used in Troll's analysis was simply the expectation of hands that were all-in before the river vs the actual result.

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Troll, is this correct? If so I missed something important.

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After thinking about it more, you could use other statistics to estimate the flaw in Sklansky bucks. For example you could estimate one's true win rate as:

EV = sEV + kW$SD

-k is an unknown constant

If you did more research you could probably better determine what factors relate EV to sEV. A multiple regression might be a good idea.

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The k and WSD is an interesting idea.

Do you mean multiple regression of sEV for each hand within my dataset? or for sEV's calculated from different datasets?

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There should also be an unknown constant in front of sEV.

I was suggesting a multiple regression to determine EV. sEV would only be one of those factors.

So your final estimate of EV would be:

EV = k_1*sEV + k_2*factor_2 + ... k_n*factor_n

You could rewrite this equation to estimate the flaw in sEV:

EV - k_1*sEV = k_2*factor + ... k_n*factor_n