*Originally published in Bluff Magazine, January 1, 2008.* reprinted with permission from Stox/BluffWhile this article will discuss the strengths and weaknesses of different learning strategies this article itself is not intended to present a comprehensive learning strategy, but rather to provide the reader with information regarding some of the more common methods for learning poker so that they may better interact with them in developing and managing their own poker game.

The first point I will need to discuss is “what is good poker?” Many people have many different and conflicting opinions about what “good poker” (hereafter abbreviated to “GP”) may be, but, so long as your goal in playing poker is explicitly to make money, GP, in terms of table play, is correctly defined by one (and only one) statement: “Good poker is the ability to accurately quantify (guess) the likelihood of your opponent’s actions

and potential future actions, and to then use mathematics to find the line (series of actions) with the highest average rate of return.”

GP (and every decision in poker) can then be split into two parts: 1) accurately guessing the likelihood of your opponent’s actions and potential future actions and 2) applying the line with the highest average rate of return. Note that by doing part one of the definition as well as possible and part two of the definition perfectly based on the assumptions of part one you will earn the most amount of money possible playing poker.

The definition of GP is somewhat similar to David Sklansky’s “Fundamental Theorem of Poker,” which states that whenever you take an action different from the actions you would take if you could see your opponent’s hole cards you show a loss. It is important to remember, however, that as poker players we have imperfect information and that in learning poker we should not be trying to understand how to play “perfect” poker (Fundamental Theorem of Poker) but “optimal” poker (GP), meaning that we will have to understand how to make the actions with the highest rate of return based on the information that is actually available.

As an example: say you are playing in a hypothetical game where a friend of yours raises all-in. Because you are familiar with your friend you know that when he makes this play in this hypothetical game he will always have either have pocket aces or exactly deuce of clubs three of hearts. If you are getting 1:1 to call his raise you should fold, even the times when he is actually holding deuce three. This is because you have no information regarding when he is holding exactly deuce three,

and so must choose the action with the highest average rate of return based on the information that is actually available, which in this case is that, on average, when your opponent makes this action he holds deuce three 14% of the time.

The first part of GP is in many ways the more challenging one. This is because guessing the likelihood of your opponent’s actions or potential actions is a non-deductive process, and ultimately all your assumptions of what you

think your opponent is likely to do, regardless of how much information you have, are simply opinions of what he or she is likely to do based on your past experiences with him or her and other opponents.

This is something which brings up an interesting problem for those learning poker: “How can I quantify the quality of my assumptions?” Since this is an intuitive, or inductive, process you can never determine the likelihood of your opponent’s actions with deductive certainty, but this does not mean that you cannot deductively evaluate the quality of your own decision making process. Careful and honest evaluation of one’s own decision making processes can often inject a much higher degree of accuracy into a player’s assumptions by making sure that the information available is being processed sensibly and rationally. What information is available to you? Would it be possible for you to get more and, if so, how? Did you have enough information to weight your opponent’s actions as heavily towards meaning one thing as you did? Was all of the information involved in your decision pertinent to the actual situation at hand? And so on.

The second portion of GP, however, is a deductively valid process, in that for any set of assumptions made regarding the likelihood of your opponent’s actions

you can use mathematics to find the one line that will have the highest average rate of return based on those assumptions. This may not always be a simple thing to do, of course, but there is quite a bit of literature and software available to help familiarize players with the

mathematical aspects of poker, and while it may not always be practical to solve mathematical questions in entirety many players may find that it only takes a little bit of handy-man’s know-how to be able to solve simple questions that let them see what sorts of factors have a large and small impact in particular situations, and how changes in different factors would affect how you would want to play the hand.

And so, having discussed what GP is, this brings me to my next point: what are some of the common problems with the ways that people are trying to learn poker today? I’ve already somewhat covered the issue with trying to play perfectly based on what your opponent is actually holding. It’s very important to remember that in playing poker you are not trying to play against your opponent’s actual cards, but to make the series of plays with the highest average expected rate of return based on the information that is actually available. This means that most of the time you are not playing against two specific cards, but a number of potential hands. This also applies to trying to quantify the likelihood of your opponent’s actions, wherein you need to determine what actions are likely and the degree of that likelihood based on the information that is actually available and not the action he or she ends up making in actuality.

The second issue I’m going to discuss is not necessarily a problem in and of itself, but is something that most people should be aware of, particularly when moving on to more advanced play. This issue is that, traditionally, the angle that most people take when trying to teach poker, be it through books, a website or one

on one instruction, is to try to instruct the student on how to play a generalized, exploitative game plan based on common assumptions of what people are likely to do. The reason that I take the time to say that this is not necessarily a problem is that the learning curve for poker

is very steep as is and it would be very difficult to approach a new player with the tools to take a more mathematical approach to finding optimal actions against their opponents on an individual basis.

It is important to remember that, while it may be an effective method for instructing beginning players, this method of learning contains some extremely large flaws. A method of instruction that centers on teaching the student how to exploit particular game conditions is only effective so long as those game conditions remain true. If game conditions change or are altered the instruction that the student has received is no longer effective, and as is the case with many amateur players these exploitative concepts may be misapplied to different game conditions.

On a similar note, it is also important to remember that even the best generalized advice only provides the optimal action as often as the conditions which the advice assumes are true. If a particular school of thinking prompts you to take an action which will have the highest

average rate of return based on the information which is actually available (rather than the generalized assumptions which the school of thinking takes) 80% of the time (meaning that the other 20% of the time, on average, the conditions which are assumed by the generalized advice are not true) the student will show a higher profit making these actions than if he or she were to do the opposite, but in approaching higher levels of play, however, this rate of success may no longer be

sufficient, and the student will eventually have to begin to strive to identify the actions with the highest average rate of return based on the information which is actually available in order to achieve the highest rate of return possible.

And finally, what seems to be the most common problem with how people learn poker today is that the majority of poker discussion ultimately amounts to asking “how likely is my opponent to take such and such an action.” This is not necessarily how the majority of questions will be phrased, but the mathematical components of many of the hands that players spend a great deal of energy thinking about are easily solved. For example, say an

opponent bets pot on the river, and you would like to know if you should call getting 2:1. This is a good example of a question which everyone with a rudimentary poker background knows how to solve, but is the sort of question that is asked time and time again.

The issue with these sorts of questions is that, in general, the ability to accurately quantify the likelihood of your opponent’s actions and potential future actions is not something that can be effectively taught by instruction, since, again, it is a non-deductive process. While it is perhaps better to have asked this sort of question and received an answer than to not have asked at all many players, even at very advanced levels, place far too much of a stress on debating these largely circumstantial issues, and it may often make little sense to ask people who did not have access to all of the information that was potentially available, such as previous hands, what they thought your opponent’s actions were likely to represent. Ultimately, I believe a player has to accept that they will have to play some measure of poker in order to accurately determine the likelihood of their opponent’s actions, and this is a skill best acquired through experience.

If the first portion of GP is largely unteachable then most of the focus for learning and teaching poker must fall on the mathematical component. Some of the most productive poker discussion stems from people sharing methods to quickly and easily “solve” common mathematical questions. By placing the stress on understanding what actions are optimal under different assumptions and exploring what conditions have to change in order for different actions to become optimal a student cannot only process the data that is presented to him or her more efficiently but will build a much more complete, accurate and adaptable poker game. This may seem like an intimidating process, but the tools are available. The incentive to taking this approach is

quite high as well, because if you are always able to find the line with the highest average rate of return based on your assumptions it is not difficult to spend quite a bit of time earning money playing poker, and the more poker you play the stronger and stronger you ability to accurately quantify your opponent’s actions becomes, and you will be playing a lot of very good poker.