[BillChen]

On one extreme is the game where your opponents strategies are entirely known and they have no adaptive abilities. In this case it's relatively straightforward to calculate the best play. Jerrod dubs this the PlayStation (tm) approach to poker. We do go over several examples of this in Section II. Even though game theory is the biggest section in the book, the book is hardly all about game theory. It's just that in comparison the mathematics of playing against a known strategy is much easier. This is not to say that the sections on how to collect data against your opponent and Bayesian inference in tells aren't important--in fact, they are more useful against weak and unadaptive opponents.

But even in so called "soft" games the players are not this predictable. Even when it's claer someone plays badly because of a given play it's still unclear how badly they play. For example say you see someone make a bad call, do you know if it's the minimum hand they would call with or will they call with worse, or did they just make the call on a whim? There are certainly situations where game theory may still apply such as value betting on the end.

Even if you read your opponent perfectly for a mediocre hand--in the book we call this the clarvoyant game, if you don't have an idea of his calling frequency you may still want to play the optimal mix of bluffs and value bets at the end. This is the strategy that is the hardest for your opponent to play against.

Bill