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posted March 24, 2009 at 16:50 EST in Poker School Tips & Strategies

Game Theory and Poker Part 2

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Optimal Play & Exploitative Play

This is the second article in a series on the topic of game theory and its applications to poker. In the first article, Game Theory and Poker Part 1: Introduction, I gave a brief summary of what game theory is, what it can do, and a little bit about how it relates to poker. I also gave you an example of one “optimal” strategy; in the game rock, paper, scissors, an optimal strategy would be to randomly play each option 1/3 of the time. No matter what strategy your opponent adopts to counter yours, you will always break even. In this article, I’m going to explain the opposite concept, “exploitative strategies,” and then compare them to optimal ones.

Exploitative poker strategies

I’m sure you’ve heard it before: “poker is all about mistakes.” “You need to make fewer mistakes than your opponents,” “you need to capitalize on your opponent’s mistakes.” Almost everything that’s published (on the web and in print) is based on this “mistakes” approach to poker theory. And it’s not wrong. The profits a good poker player makes are directly related to his opponents’ mistakes. Learning how to take advantage of these mistakes is called “exploitative play.”

Here are some examples of using an exploitative strategy in a poker game: 1) You’re playing against a player who bluffs compulsively. You had an ace high flush draw, but missed. Your opponent bets on the river. In this situation your normal strategy would be to fold, but against a habitual bluffer, you alter that strategy and call. That’s an exploitative play. 2) You have ATo on the button. The cut-off (the player to your immediate right) opens the action with a raise. Normally, you would make an isolation raise, however, your opponent is extremely tight before the flop, so you have to fold. This is also exploitative play.

It’s really important to learn how to adjust to your opponents’ mistakes, I’ve written many articles about it (adjusting to passive opponents, loose opponents, tight ones and over-aggressive ones. However, game theory has nothing to say about exploitative play.

Optimal poker strategies

Playing great poker isn’t just about making these adjustments, exploiting your opponents’ mistakes. There’s also your baseline strategy, the thing that you’re adjusting from. This baseline strategy tells you what to do if your opponent isn’t bad, doesn’t make a mistake, if you don’t have to adjust. And it’s here that game theory can help you. The goal of your baseline strategy is to balance it so that other players can’t make profitable adjustments to you, even the very best players.

A perfect game theoretic strategy could never be exploited. Your opponents could make all the adjustments in the world and it wouldn’t make a difference. If you only played that strategy without ever playing exploitatively, you wouldn’t make much money (you’d make some profit when your opponent made a basic mistake, one that isn’t part of any optimal strategy). However, at worst you will break even in the long run (ignoring the rake), even against the best players in the world. Game theory can develop your basic strategy, the one you use against really good players who don’t make (very many) mistakes, the one that you make adjustments to bad players based upon. Improving that basic strategy will have a real effect on your bankroll.

Unfortunately, poker is too complex a game to come up with a complete, optimal solution for it. Even computer programmer-mathematician geniuses (who are definitely working on the problem) are nowhere close. Apparently, they have come close for heads up Limit Texas Hold’em, but with more than two players it gets too complicated.

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So game theory can’t give us our entire strategy, but we can still use it to work on certain, smaller, simpler parts of our entire strategy. That’s what we’re going to do in the next article, Part 3: Optimal Solutions – Bluffing Frequency. You’ll learn how to create a strategy for when to bluff that is completely optimal.

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