in response to olliepa's post regarding game theory and analysing villain's actions post flop...
Correct - we require an opponent model in order to assess EVs correctly, and the model needs to be specified in terms of how each villain acts on each street based on their relative hand ranking (relative to the board - not the absolute post flop hand ranking). Here I'm referring to categories such as overcards, overpairs, Top pair top kicker, gut shot draws etc. For the opponnet model was also need to consider, the current street, who the prior street aggressor was, the texture of the board, the bet actions based on whether villain is IP/OOP, and the Stack Pot Ratio (to list just a few of the key statistics that influence a player's actions). Ignoring multi-way post flop action for now, then we can deduce how big the opponent model matrix needs to be:
1) If we have a handful of common player types (say 12),
2) 3 streets,
3) 22 (say) relative hand group bins,
4) 3 prior street aggressor categories(as the prior street aggressor, vs, no prior street aggressor),
5) 19 possible bet actions based on position,
6) 3 board textures (wet, neutral,dry) and
7) 3 (say) SPR categories...we quickly see that the real problem isn't the EV calculation but deducing an appropriate opponent model. To make matters worse even if we have access to billions of hands, only about 5% go to showdown and these are very biased. Hence we would need to unpack the biases to get a reasonable representation of plausible player actions.
Of course the opponent model can be approximated.
One interesting finding I've come across is that approximations aren't too bad, partly because the difference in EV's across different options is actually often pretty small. Effectively there are quite a few spots where raising, calling or folding have very similar EVs of around zero...or at least where the 90% confidence interval of the EV for hero's action overlap with other possible options.