Today on the Zoo I interview Dr. Brian Space, scientist and 2+2 poker writer. Dr. Space came to my attention after Matt Berkey tweeted out the article “GTO, the Value of Information, and the Nature of the Solution to No-limit Hold ‘em,” which supported Matt’s long-held contention that “GTO” poker is not nearly fully explored even in the age of solvers. While I had never spoken to Brian before, we do have a small connection, as both of us are members of the DGAF community forum.
This is an unexplored avenue. Such a strategy removes an additional constraint and provides for significant additional information hiding. In discussing ranges above, it was implicit that ranges bifurcate and split even into more discrete parts as the game tree is explored. We might have a river spot where our full houses and simulant bluffs bet one sizing, while straights make a significantly smaller wager. Indeed, optimal solvers find such spots to be ubiquitous and even find that one should randomize certain holdings between the bet sizing ranges. In the new paradigm there is a probability associated that the nut-flush in the above spot might sometimes bet with the full house sizing and another percentage of the time with the straights. Current strategies allow for leakage of information that is far from optimal. It is easy to imagine bet sizing distributions with significantly overlapping tails that make our opponent’s life in guessing our intentions miserable.
While solvers already show strategies with “overlapping tails” and just as importantly, we can theorize and and execute these and other principles to reasonable effect, Dr. Space is seeing a bigger picture where more EV is gained when moving beyond discrete bet sizing constraints. My question to him was, essentially, does it matter given what we can do with the tools we have?
The pod graphic is based on Dr. Space’s CO2 over N2 sorption animation.