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I put up some new data, from a 10M-hand sample. (These files are pretty large, 236KB for the backs, 356KB for the middles, and 28KB for the fronts.)
http://www.lowballgurus.com/cp27/10M-backs-2.txt
http://www.lowballgurus.com/cp27/10M-middles-2.txt
http://www.lowballgurus.com/cp27/10M-fronts-2.txt
http://www.lowballgurus.com/cp27/10M-backs-3.txt
http://www.lowballgurus.com/cp27/10M-middles-3.txt
http://www.lowballgurus.com/cp27/10M-fronts-3.txt
I put up the distributions from two different iterations over the same set of hands, to illustrate how the maximally exploitive strategy switches strength between the front and the back/middle. There are about 2% fewer pairs in front in "3" than in "2".
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So, is this just oscillation, or is the "3" set better than the "2" set?
At this point, do you think that this data is an accurate reflection of the percentiles of hands we would see in the front/middle/back in people that play well (or, among well-played hands in some sense)?
I guess there's an overall question of, "what should we conclude from this awesome data"? I love your algorithm... it would be interesting to see if this method applied to traditional CP would yield the same results as Smolen. Someone posted the 10th, 20th, ... percentiles for the front hands in CP (from Smolen?). Would this algorithm produce the same results? Would it be easy to run a 100k trial as all high?
In any case, thanks for the excellent work.