It’s easy to be impatient during the poker learning process – we all want to get better at poker as fast as possible, win all the money and reach the game’s highest heights. We all want to soak up as much knowledge as we can, and put it into practice as fast as possible. But trying to force the process can be as dangerous as taking it too easy – after all, there’s only so much information we can digest at over a short period of time.
On top of this, the more information we digest at once, the harder it becomes to put all of it into practice – even if we remember the information, actually acting on it in-game is another question entirely. In order to facilitate both these processes – the process of taking in information, and the process of utilizing it to our advantage – we need something in our arsenal to make the whole thing easier. This is where heuristics come in.
What is a heuristic?
Mirriam-Webster defines ‘heuristic’ as an adjective meaning ‘involving or serving as an aid to learning, discovery, or problem-solving by experimental and especially trial-and-error methods’. It can also be used as a plural noun – i.e. the field of heuristics – but it has another definition that’s more appropriate for our purposes.
In computer science and high-level mathematical optimization fields, an heuristic is a ‘shortcut’ solution to a problem so complex it requires a lot of time and energy to solve. This is where poker comes in – we can immediately see how deep computer science and poker may cross over in this regard. They’re both highly-complex fields involving a myriad of mathematical elements, almost all of which are impossible to accurately define using only a human brain.
If you’ve ever run a Nash equilibrium or GTO solution calculation for a poker hand, you’ll know that the results of these calculations can be extremely complex – at best, a preflop shove chart will give you answers that are difficult to memorize and not precisely applicable to real-game situations, and a postflop GTO solution will likely involve such mixed frequencies for each action that we can’t possibly act on its advice without simplifications.
Developing and applying poker heuristics can help us to evolve our game to a new level, by combining our accumulated experience and understanding of the player pool in our games, with a sound understanding of poker theory. They allow us to adopt a playing style built on a rock-solid foundation, but with room for adaptation based on circumstances, and best of all, they can be expressed, memorized and utilized very succinctly.
Some basic examples
A very simple (perhaps overly simple) example of a poker heuristic might be something like, “when we’re the preflop raiser, we should usually continuation bet most flops”. This is perhaps too broad to produce any meaningful improvements in our game if we’re already relatively experienced, but for a total novice, this would be good advice. To go one step beyond that, we might adopt an heuristic that says something like, “our continuation betting ranges should usually consist of stronger and weaker hands rather than middle-strength holdings”, and another step further beyond that might be, “our continuation betting frequencies should get progressively higher as our range advantage on the flop gets bigger”.
That last one is definitely more complex, but all three are supported by GTO calculations, and would be provable if we took the time to do the calculations themselves. They’re not hard and fast rules, and they’re not applicable in every situation, but if you follow them reasonably well, your game will be off to a good start.
We can even build on these foundations to apply a secondary heuristic in support of the first one – let’s say we know we have to c-bet more often on flops where we have a range advantage, but we don’t know how to figure out what our range advantage or disadvantage is on a given flop. There are two heuristics that might help us here – firstly, something like “the player who has the tighter preflop range will usually have the range advantage” is quite reliable, and secondly, we could also use “the more dynamic the flop, the harder it is for any player to have a big range advantage”. Both of these heuristics, again, are supported by GTO calculations.
Applying heuristics to more complex situations
Where heuristics really come in useful, is when we reach the later streets. Obviously, the deeper we go into a hand and the closer we get to the river, the more complex the hand will usually become – every decision made by a player changes and narrows their range, and thus the nature of that range often becomes harder and harder to pin down or describe accurately without running the numbers.
An heuristic that comes in very handy on the river, for example, is to recognize that the more polarized our betting range, the bigger our bet sizing should be. This is supported by GTO theories and calculations, and applies in a great many situations, particularly on the river where there are no more cards to come. Indeed, the concept of ‘polarization’ of range is almost a heuristic in itself already – to describe a range in a single word is to reduce a complex mathematical equation to a simple, easy-to-understand concept.
Developing your own heuristics requires a lot of hard work and analysis, often requiring access to a GTO calculator of some kind, but it can also be useful to take whatever you can from training videos, Twitch streams or other content and try to observe patterns in what most players tend to do. If you notice very good players consistently doing a specific thing in a specific type of spot, consider whether there’s any one specific reason why they might be doing that. If you find something, try putting it into an “if X, then Y”-type sentence, which might help you easily and efficiently incorporate that tendency into your play.
Don’t get stuck in a rigid framework
Finally, while heuristics are a great way to bypass the need for absurdly complex mathematical approaches in-game, they’re not the be-all and end-all. From time to time, your heuristics will let you down if you apply them too universally, and you’ll miss out on opportunities to gain extra value by deviating from the norm.
In essence, you’ll become ‘robotic’ in your play, and you’ll be on autopilot – this is the death knell for a poker player’s ability to make money. The days where robotically mass-tabling online games was a profitable business model are gone, and even if you’re playing in extremely soft low-stakes games, there’s no cogent argument to suggest that autopilot is ever the best way to play.
Developing and applying heuristics to speed up your poker learning requires hard work, attention and in-game focus, just like anything else. Unfortunately, while there are smarter ways to work, there’s no substitute for working hard, and there are definitely no shortcuts to long-term success.