Concepts of PS

Flop clustering​

In Texas Hold'em Poker, there are 1755 different possible flops. Grouping or "clustering" these flops allows us to simplify our gameplan by treating different flops with similar characteristics the same way.

But which method of clustering represents all possible flops the best?


We performed different tests where different parts of ranges played against each other like "25% top range vs. 25% top range" or "33% bottom range vs. 66% bottom range" to figure that out. Measuring the average error per hand to the size of the subset gives a function with a 1/x behavior: 

As you can see, GTO+ and PioSolver do a great job of finding clusters where the average error converges to 0 quite fast. The gap per subset-size is related to different subsets with the same size. 

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