In this video, SplitSuit breaks down the 4 types of exploitation most common in poker. These come directly from "w34z3l's" PRO video "Exploitation Fundamentals" and break down the big things that you want to be looking for in every session. While fishy players have gaps in their strategy large enough to drive a truck through, even strong players have areas in their game that allow you to find & exercise +EV exploits.
Comments
One of the most ignored topics in poker is the problem with classification. You think you can safely label someone Aggro, TAG, LAG etc. Really? How robust are your observations? Why don't you walk through ALL the factors that are necessary to arrive at that conclusion like sample size, the context of that observation (players to left and right), table-image given a certain collection of players, etc., etc. It's fun to believe you have a definitive read and that now you get to go into exploit mode. Most of the time, the validity of that read is lacking particularly with sample sizes of only a few thousand hands. Some of the time you are the one who has been exploited in your desire to be exploitative.
This is a totally fair point, and really where we get into the art and science of the game. Making assumptions doesn't guarantee that the assumptions will be perfect. But with experience, player pool analysis, and a solid technical foundation - the ability to make better assumptions increases dramatically. That said, the sample size will always be lacking and there will always be a margin of error in the assumptions. And if players aren't willing to accept that margin of error, they can always attempt to implement a more balanced approach so long as they understand they are far from optimal in 99% of games.
I agree for the most part. But the thing is there are a lot of spots that are 0 EV at equilibrium using a GTO strategy. And those that case, IMO we might as well work off of flawed, failiable assumptions and try to do better then make a bunch of 0 EV decisions. Making an educated guess and being wrong in our assumptions sometimes is better then breaking even in a spot.