# Poker Gto Definition

- Poker Gto Definition Dictionary
- Poker Gto Definition List
- Gto Definition For Poker
- Poker Gto Definition
- Poker Gto Definition Meaning

I don't have hard proof, since the GTO strategy for poker is not known, but my guess is that the GTO strategy for poker would be able to easily exploit weaker players. For example, if someone decides to add fold AA pre every time to their strategy, they're 100% losing money. The term GTO is becoming more and more popular. Although the theory of GTO has been discussed for many years, its popularity within poker is peaking right now. A common way to explain how GTO works is based on the game Rock, Paper, Scissors. However, if we did get there (perhaps because Villain played a non-GTO strategy), we could find ourselves folding the nuts despite playing a GTO strategy. This is a pretty good example of how the normal English meaning of “optimal” conflicts with our definition. Game theory optimal (GTO) poker is an umbrella term players use to describe the holy grail of no-limit holdem playing strategy, by which you become unexploitable to your opponents and improve your winrate. Gordon Ramsay Cooking I. Looking for online definition of GTO or what GTO stands for? GTO is listed in the World's largest and most authoritative dictionary database of abbreviations and acronyms The Free Dictionary.

*This is Part 1 of 6 of an adaptation of my chapter “Game Theory Optimal Strategies: What Are They Good For?” from Excelling at No-Limit Hold’em edited by Jonathan Little.*

Much of the reason I wrote Expert Heads Up NLHE was to explain the ideas of game theory, poorly understood in the community at the time, to the average poker player. Heads up no limit (HUNL) is my game of choice personally, so it made sense to use it as the primary example. However, HUNL is something of a simple case, and there’s a bit more to be said about how game theory applies to other games. In this chapter, I’ll give a quick introduction to game theory as it applies to a variety of common poker formats. We’ll see when it’s useful, and more importantly, when it’s not – when it’s appropriate to use game theory-inspired strategies, and when it just can’t really guide our play. I promise to cover a practical skill or two as well.

### Games, Strategies, and GTO Strategies

So what is **game theory optimal** (GTO) play? First of all, people tend to get hung up on the word *optimal*, so I want to dispell some common misconceptions. Imagine this – there’s some mathematician. She’s made up some potentially useful concept with a moderately complicated definition, and she wants to discuss it with other people. What does she do? Well, first, she probably needs to give her concept a name. That way, she can just say, “Suppose I have a continuous function instead of “Suppose I have a function such that, at every point on its domain, the limit of as approaches in the domain equals .” Much easier, right? Now don’t worry – you don’t need to know anything about functions, continuous or otherwise, to read this chapter. The point is that the word “continuous” wasn’t made up from scratch – it was a pre-existing word in spoken English that means something only vaguely related to what the mathematician actually wants you to think about when you hear “.

The “O” in GTO is like that. There’s a very specific technical definition for “GTO strategy” which we’ll get to shortly. We could have decided to call these strategies crunchy or yellow or Vulcan, but hopefully game theory optimal is a little more evocative of what we mean, even if it isn’t perfect. So please forget any preconceived bias you have about the word optimal. In this chapter, GTO means exactly the following, no more and no less.

Ok so suppose you have some players playing a game, and you have a set of strategies (one for each player) such that no player can improve his EV by changing his strategy. Then, we say that any one of those players’ strategies is a GTO strategy for that player in that game. Great. In a minute, we’ll tease out some consequences of that definition: what special properties such a strategy has, etc. But first, if you’re paying attention, you might feel like you’ve been cheated! I told you that “GTO” has a very specific technical meaning, but then I gave you a definition that relies on more fuzzy terms: **game** and **strategy**. As you may guess, we mean something specific by those terms as well. Let’s talk about those ideas and then come back to GTO. We’ll say something more about EV in the future as well.

I’m going to tweak the next couple definitions a little bit to make them more useful for poker. For us, a “game” will correspond more or less to a single hand. It is composed of the following four things. It’s:begin{itemize}item A set of playersitem Starting ranges for each playeritem A **decision tree** that describes all the possible sequences of actions that the players (and **Nature**, i.e., random chance) can take, anditem Payoffs that describe how much money or chips or value each player has at the end of the hand, for every way the hand can endend{itemize}When we describe a game, we’ll also usually want to specify the starting pot and stack sizes of each player, although presumably we could find them by starting at the bottom of a decision tree (at the end of the hand) and working back up the series of actions to the beginning, tallying bets as we go.

A player’s range tells us the different hands he can hold as well as how likely each of them is. A player’s starting range is his range at the beginning of the game. Of course, a player’s possible holdings at the beginning of a holdem hand are well-known, so we often won’t need to specify them. However, we’ll sometimes find it convenient to set up sort of artificial games that describe play over just part of a hand. For example, we could draw a decision tree that describes play on just a single river. In that case, we’ll need to specify the ranges of each player at the start of river play to fully describe the situation.

I should say what a decision tree is! A picture is best. Check out the figure below. This picture corresponds to a game with 3 players, named BU, SB, and BB. There are two components in the diagram: circles and lines. Each circle in the tree represents a spot where a player has to make a decision – we call them **decision points**. More specifically, each decision point corresponds to a distinct set of **public** information – the information you’d have available if you were a third party watching the game (with no hole card cam) – basically everything except the hole cards. I’ve labelled each point with the name of the player who owns it, i.e., who gets to make a decision there. Each arrow leaving a point represents an action the player can choose, and when he takes an action, the game moves to the point indicated by the arrow.

The game begins at the top of the tree. (Here, I’ve neglected to draw actions for posting blinds, but they’re implied.) Then, BU can fold, call, or raise. If he folds, the SB also has the options to fold, call or raise. If the SB calls, the action moves to a point owned by the BB. And so on. Points all the way at the bottom of the tree (which are arrived at the end of a hand, i.e. at showdown or after all but one player folds) are known as the **leaves** of the tree. (Get it?) A tree describing all of the possible lines, including all future streets and and so on, would be a bit unwieldy, so I’ve left dangling arrows to indicate places where much more lies below, undrawn. You can imagine how it would go.

So that’s a game. Strategy is another word that has an English meaning that’s close to but not quite the same as its technical definition. For us, a strategy for a player is something that tells him exactly how to make every decision he could face in the game. Practically, it tells him, for every one of his decision points and every hole card combination that doesn’t conflict with the board, how he will choose between each of the options available to him there. Now, we could imagine some fairly convoluted decision making processes, but we’ll generally restrict ourselves to one of the two following types. If a player takes one action all the time (with a particular hand at a particular point) we say he’s playing a pure strategy there, and if he chooses randomly between multiple options with certain probability (say fold and call ), then he’s playing a mixed strategy.

Now, if we know a player’s strategy, we can find his range at any point in the game. We have his starting range, and then at each of his decision points, he splits the range with which he arrives there. He chooses an action to take for each component of his range. If we know a player’s range for taking each action, we can often more or less work out his strategy. For example, if we know he arrives at a point with of a hand, and his range for taking one action includes of the hand and the other includes , then we can reason that at that point, his strategy involves taking the first action three-quarters of the time and the second one-quarter of the time. However, if a player arrives at a point with of a hand (because his strategy is such that he never gets to this spot with this hand), then all of his subsequent action ranges must also contain of the hand. His strategy, by definition, must dictate his play here, but we can’t use his ranges to figure out his frequencies.

So if we know a strategy, we can find the ranges, and if we know ranges, we can work out parts of the strategy – those that we might consider most important – the parts that describe play in spots the players can actually get to when they play their strategies. For practical purposes, when we describe players’ strategies, we’ll usually talk about their ranges, but to be clear, they’re not exactly the same thing.

Great, now we’re ready to revisit GTO in full force. So again, a set of strategies is GTO if no player can unilaterally deviate and increase his average profit. An equivalent way to put this is to say that every player is playing **maximally exploitably** (i.e. as profitably as possible), given his opponents’ strategies. So, if all players but one in a game are playing strategies from a GTO set, then the last player can do no better than to also play his strategy from the set. A set of GTO strategies is also called an **equilibrium** or a **Nash equilibrium**, and if all players are playing their strategy from an equilibrium, we say we’re **at equilibrium**.

Let’s take a look at one consequence of these definitions that many players find counterintuitive. This isn’t super important in and of itself, but it’ll help us to become more familiar with the concepts. *A GTO strategy can involve folding the nuts, even on the river.* Suppose we’re at equilibrium. No player has any incentive to change his strategy. Imagine taking Hero’s strategy in a spot that play never reaches and tweaking it so that it folds the nuts a small amount of the time. By “small” here, I mean that we don’t start playing poorly enough that our opponents actually can improve their EV by switching up their play to arrive at that spot. Well then the tweaked strategy is still GTO, since it’s still the case no player can increase his EV by unilaterally deviating. Folding the nuts on the river doesn’t affect our EV if it’s in a spot we never get to at equilibrium. However, if we did get there (perhaps because Villain played a non-GTO strategy), we could find ourselves folding the nuts despite playing a GTO strategy.

This is a pretty good example of how the normal English meaning of “optimal” conflicts with our definition. Few people would call folding the nuts on the river optimal, but such play is consistent with a GTO strategy. By the way, notice that in the previous paragraph, we imagined constructing two distinct strategies for a player, and we said both were GTO. Indeed, there is no reason to think that GTO strategies are unique, and they’re often not. This point will become important for us shortly.

## Poker Gto Definition Dictionary

The next section, GTO Play in Cash Games and Tournaments, will be posted eventually, and the full book is available now:Excelling at No-Limit Hold’em.

As new depths of poker strategy continued to be discovered, Texas holdem

tables sound more like science labs than the scene of a simple card game.

Thinking players in today’s game casually toss out references to balancing or

merging their hand ranges, applying an “exploitative” approach to take advantage

of “suboptimal” strategies, and of course, integrating “game theory optimal”

plays into their arsenal.

Perhaps more than any other advanced strategy concept, the notion of game

theory optimal play – better known as GTO – has seeped into the mainstream poker

consciousness. Players of every skill level have at least familiarized

themselves with the idea of making their own game GTO, but as with any other

ubiquitous term, the exact definition of poker’s newest buzzword differs

depending on who you ask.

The steady advancement in the way players tackle Texas holdem problems is

only natural, as the Poker Boom of 2003 to 2006 prompted millions of thoughtful,

intelligent, and analytical individuals to take their talents from the classroom

to the card room. The merits of that choice are debatable on the individual

level, but what can’t be disputed is how the new generation of poker students

ultimately became masters of the field.

Eschewing traditional advice about “playing the man, not the cards,” young

poker players today focus their minds on the mathematical underpinnings of Texas

holdem gameplay. By using hand distribution to equity calculators like the Poker

Stove product, basing every possible decision on the all important variable

known as expected value EV, and scaling back the standard opening bet from three

times the big blind, modern Texas holdem experts have fundamentally altered the

game’s very foundation.

For beginners just now entering the world of Texas holdem, or even old hands

who simply struggled to keep up with the game’s accelerating advancement,

hearing smart and savvy opponents reference ideas that sound more like calculus

homework than a card game can be quite intimidating. It’s hard enough figuring

out what to do when you get four bet holding pocket jacks, so the thought of

learning about intricate game theory constructs and the higher level reasoning

behind GTO plays can be daunting to say the least.

With this page, we don’t purport to be PhD holders or even Texas holdem

experts, but rather recreational players like yourself who simply wanted to

learn more about game theory as it applies to poker. In keeping with the

instructional theme, we’ll offer a syllabus of sorts, starting out with a basic

glossary of the key terms and concepts you’ll hear repeatedly during any

discussion on GTO play. Next up you’ll find a section detailing several common

examples, written from the perspective of a poker player, that help to

illustrate the technical terms described earlier. From there you’ll find a list

of applicable resources – written or developed by successful high stakes

professional players and game theory experts – through which you can pursue an

advanced education.

## Glossary of Game Theory Terms

Before we move on to the descriptions, it’s important to discuss what the

concept of game theory really means.

According to Roger B. Myerson, whose introductory textbook titled “*GameTheory: Analysis of Conflict*” was published by the Harvard University Press in

1991, game theory can be defined as “the study of mathematical models of

conflict and cooperation between intelligent rational decision makers.”

As you can see, this definition doesn’t mention anything at all about poker

or Texas holdem. That’s because game theory is applicable to any game or contest

which involves decision making on the part of players combined with access to

partial information. Additionally, the ideas put forth by game theory experts

have also been co opted for use by economists, political scientists, biologists,

and several other fields of study. Thus, while the study of game theory is

predicated on the various rules and procedures used to govern classic games like

Texas holdem, the ideas that emerge from game theory investigation are widely

applicable across a diverse range of subjects.

Although game theory wasn’t codified as a field of study until the 1920s,

evidence of GTO approaches to basic card games can be found dating back to the

early 1700s.

In 1711, Charles Waldegrave wrote a letter to his brother outlining a

“minimax mixed strategy” to the simply two player card game known as Le Her.

In 1913 a German mathematician named Ernst Zermelo developed “Zermelo’s

Theorem,” which states that

“In any finite two person game of perfect

information in which the players move alternatingly, and in which chance does

not affect the decision making process, if the game cannot end in a draw, then

one of the two players must have a winning strategy.”

As you might suspect, this

long passage was used by Zermelo to describe chess, which he successfully proved

to be a “strictly determined” game from a strategic sense.

Throughout the 20th century, mathematicians and logicians like John von

Neumann, Oskar Morgenstern, Merrill M. Flood, Melvin Dresher, and John Nash each

contributed fundamental theories and postulations to the field of game theory

study.

For poker players with an educational background in advanced mathematics – of

whom there seemed to be an endless supply during the Poker Boom – learning the

lingo of game theory and applying it to their favorite game proved to be a

highly beneficial proposition. These players were able to expand their lines of

thinking beyond the most basic constructs – what do I have or need, what does my

opponent have or need, etc. – to turn a seemingly simple poker hand into an

exercise in statistical modelling and probability based prediction.

But for the rest of us, the laymen at the table who haven’t memorized reams

of mathematical formulas, diving deeper into the subject of game theory study

can present a firm barrier. The average person can only take so many

abbreviations and hypotheticals before their head begins to ache, so breaking

things down to their basic meaning is a helpful way to begin.

Take a look below for a comprehensive glossary of essential terms and

concepts used within the world of game theory:

Any strategy that offers a reduced expected value EV,

compared to GTO strategy, when playing against an exploitive strategy. Any non

game theory optimal GTO strategy is, by definition, an exploitable strategy.

Any strategy that offers an increased expected value EV

than a game theory optimal GTO strategy, when playing against any particular

strategy. Any non GTO strategy that counters an exploitable strategy better than

a strictly GTO approach is, by definition, and exploitive strategy.

The strategy that offers the highest possible

expected value EV when an opponent always applies an optimal counter strategy.

The classic GTO strategy example concerns the zero sum hand game known as “Rock,

Paper, Scissors.” In this game, the GTO approach involves selecting randomly

between rock, paper, and scissors while using an equal distribution. This

strategy provides the highest level of EV, at 0.50 percent equity, against any

opponent strategy that consists of all rock, all paper, or all scissors.

The strategy that offers the highest possible

expected value EV against any opponent strategy. Returning to the Rock, Paper,

Scissors example, in a game where you know your opponent’s strategy was to throw

rock on every game, the optimal exploitive strategy would be to counter with

paper every game – because this would create an EV of 100 percent. And should

your opponent modulate to a strategy based on using rock on 50 percent of games,

paper on 25 percent, and scissors on the other 25 percent, the optimal

exploitative strategy would also be to throw paper on every game – because you’d

create a scenario in which you’d win or tie on 75 percent of games, while losing

only 25 percent of the time.

Any strategy that offers a lower expected value EV than

the optimal exploitive strategy. Back to that Rock, Paper, Scissors game, where

your opponent’s strategy is to throw rock on each game, you could opt for a 50

percent paper and 50 percent rock blend of moves. And while this would still be

a winning strategy, because you’d only win or tie, it’s performance can’t match

that of the optimal exploitative strategy throwing paper every time – making it

a suboptimal strategy at best.

### Game Types

Cooperative / Non Cooperative GameIn a cooperative game, players are

permitted, encouraged, or even required to form binding agreements with fellow

players. A game like Monopoly, in which players can negotiate the price of a

mortgage on property deeds among other agreements, is a classic cooperative

game.

A non cooperative game, on the other hand, forbids players from making

similar arrangements among themselves. Technically speaking, poker variants like

Texas holdem are non cooperative games, because the rules preclude collusion and

other forms of explicit cooperation. Even so, as you’ll learn in the next

section featuring examples of Texas holdem game theory in action, many

situations in the game compel players to form implicit agreements to achieve a

certain effect stalling on the bubble, big stacks avoiding one another with

pending pay jumps, etc..

From a practical standpoint, any game involving human

players must be a finitely long game – or one that has a fixed endpoint. Whether

that means attaining a certain score, satisfying a series of conditions, or

otherwise defeating your opponent, a finitely long game has a beginning – and a

definitive end. And even in a game designed to stretch on into perpetuity, the

limits of human endurance, and indeed lifespan, prevent it from being truly

infinite.

But game theorists have no such limitations on their work, and in the process

of investigating mathematical proofs, they’ve created the concept of infinitely

long games that are never forced to end. These games are devised, in part, to

study the relative strengths and weaknesses of dueling strategies which adapt

based on one another’s actions.

For poker players, every cash game or tournament session has a start and an

end. But as any experienced poker pro knows quite well, judging the results of

any particular session provides an inconsistent appraisal, and the truth is best

discovered by examining results over the long run. That long run can encompass

years, decades, or even a player’s entire lifetime on the felt – making Texas

holdem and other poker formats an infinitely long game in spirit.

For game theorists, a “meta game” means something entirely

different, but as a poker player, you’ll hear this expression used largely to

describe the multitude of external factors that conspire to influence every

action, hand, and session.

These factors can span the spectrum from personal history between particular

players, the relative importance of pending prize money to opponents of

different means, the impact of physical fatigue and diminished stamina, and even

the presence of television cameras or a similar spotlight.

Some players can dominate a large tournament field until reaching the final

table, where the change of setting from anonymous area on the floor to ringed

off feature table can jar their nerves. Experienced players use their knowledge

of this meta game to apply increased pressure and make things uncomfortable for

less experienced foes.

For the most part though, when a poker player mentions the meta game

affecting their decision making, they’re referring to prior history between

themselves and an opponent. Perhaps the other player has shown a propensity for

checking back strong hands in position, so you may begin using flop checks more

often to clarify his range. Or maybe you were a tournament victor to their

runner up twice before, and you know they’ll be looking to knock you out of the

final table earlier to prevent another heads up match, so you widen your range

in anticipation of them playing back light.

The concept of meta game at the poker table can go as deep as a thinking

player prefers to take it, but in many cases, if your opponent isn’t a thinking

player in their own right, the advantages gained simply aren’t all that

effective. An oblivious opponent who doesn’t even realize that they’ve played

dozens of pots with you before can’t really be exploited based on that meta

game, as they aren’t even aware that it exists.

A perfect information game

is one in which both players have full knowledge of each other’s previous moves

or actions. The classic example of a perfect information game is chess, as both

players begin with identical piece alignments and witness all subsequent moves.

An imperfect information game is one in which both players are limited to an

obscured view of the full game conditions. In blackjack, for example, you know

your own hole cards, but not that of the dealer, leading to a situation in which

making educated guesses is the only way to proceed. Texas holdem is another

imperfect information game, because even though all players can see the same

community cards on board, and their own hole cards, the hole cards of every

other opponent remain concealed until the showdown round is reached.

A zero sum game is one in which the amount of

“available resources” in play can never be changed. Poker is the standard zero

sum game, because leaving aside the house’s rake in cash games, every pot that

is played results in an equal transfer of chips. If you win 12,000 chips in a

pot, a player or players at the table must have lost 12,000 chips as a result.

A poker tournament is a perfect encapsulation of a zero sum game, as every

chip put in play throughout the proceedings will wind up in the eventual

winner’s stack. Players will transfer chips back and forth throughout the

tournament, stacks will grow, shrink, and disappear, but when it’s all said and

done, the same amount of chips will be present and accounted for when the final

two competitors begin heads up play.

Conversely, a non zero sum game is one in which the amount of available

resources in play can be changed. While playing Monopoly, for example, everybody

begins with a set amount of dollars in their bank, but factors like Chance cards

and other features can add dollars into the game’s economy without transferring

them from one player to another.

## Examples of Game Theory You Already Use in Texas Holdem

After perusing the scholarly definitions listed in the Glossary section, some

readers may be thinking that game theory is a bridge too far in terms of what

they’re willing to learn. Poker is supposed to be a fun game after all, and most

of us aren’t trained in upper level mathematics anyway, so can game theory

approaches really help the recreational player?

They can, and they already do. In fact, if you’ve spent any serious time at

the Texas holdem tables, whether in tournament play or cash games, chances are

high that you already apply game theory concepts without even knowing it.

Strategies that rely on unspoken acknowledgement of certain factors, deviations

from the norm decided on when competing against certain players – these plays

that seem instinctual are actually demonstrations of game theory in action.

We’ll run through a laundry list of commonly encountered Texas holdem

scenarios below, covering both the No Limit and Limit versions of the game, to

show you a few different ways game theory principles are routinely put into use

by beginners:

### Checking It Down to Eliminate a Short Stack

Imagine yourself playing a $55 Sit and Go tournament at your local casino.

You wind up playing your way into the final four out of nine players – but only

three players will earn a payout.

The next one to be eliminated will take home nothing for their efforts, an

ignoble end to a long tournament, but you don’t really have to worry too much

about that at this point. You sit with 7,000 chips, another has 6,800, while two

short stacks are clinging to 1,200 and 1,000 respectively.

In the big blind position, with 400 chips already committed, you watch the

shortest stack shove all in for his last 1,000. The small blind player, who is

your fellow big stack, makes the call to put the shorty at risk. You look down

at Kc 10c – a decent hand to try and bust the next player with – so you call as

well, creating a heads up side pot while the all in player sweats the action.

The flop comes down 10s 9h 7h, and the small blind checks it over to you. In

most spots, firing out with top pair on a textured flop would be advisable, as

to prevent opponents from backing into a straight or flush on the turn. But you

shoot your heads up opponent a quick look and knock the felt with your fist,

signaling a check.

The turn comes a blank with the 2d, but this time the small blind is checking

as the baby card falls. You check back quickly, and the process repeats itself

on the Kh river. Upon the showdown, you show your top two pair, but the short

stacked player flips up his J 8 with a smile, knowing his straight has beaten

one of the two hands it’ll need to fade.

But the small blind turns his 5h 3h face up on the felt, and the flush is

good enough to bust the short stacked player in fourth place. You, the small

blind, and the other shorty have each made the money – and all because you never

bet to force out the small blind’s ragged flush draw.

In this case, even though poker is a non cooperative game by rule, you and

the small blind recognized a prime opportunity to cooperate. By checking down

through all three streets, you and the small blind effectively ensured that two

hands, rather than one, would have a chance to eliminate the fourth place player

and burst the bubble.

In the game of Texas holdem, communicating your intent to join forces with

the small blind would represent a violation of the rules against collusion.

Players know this all too well, so when a check down situation like the one

described here presents itself and it invariably will on any tournament bubble

or pay jump, the agreement to check it down remains unspoken. This isn’t

cheating by any stretch, but rather an effective application of communicative

game theory strategy to ensure a higher likelihood of an optimal outcome taking

place.

### Keeping Short Stacks Alive to Apply Bubble Pressure

Expanding on the previous example, let’s imagine you’re enjoying every poker

player’s dream: sitting on a big stack deep in a multi table tournament. In this

case, you have a stack of 850,000 when the average is only 300,000 – and 29

players remain with the final 27 getting paid.

A look around your table presents a beautiful sight, as four of the six

opponents across from you are riding short stacks of 100,000 or under. With the

big blind set at 10,000, they’ll be forced to move in with marginal hands, which

should make them ripe for the picking as you attempt to burst the bubble with

your big stack.

You begin raising several hands in a row, hoping to get involved with a short

stacked player and take your chances on a gamble. This tournament is a big one

for your bankroll, and landing a cash on your Hendon Mob record at this level

would be quite the accomplishment, so you’re intent on busting one of the

shorties in short order.

The vulnerable players aren’t biting though, and your raises are receiving

nothing but folds around the table. The four short stacks are playing it snug,

each hoping to keep enough chips in hand to sneak into the money. As for the two

bigger stacks, they remain fearful of entering pots against you – the only

player who can bust them.

As you relentlessly raise, and the table keeps passively folding, you keep

dragging seemingly small pots which contain the 5,000 chip small blind, 10,000

chips in the big blind, and another 7,000 in antes at 1,000 chips each. That’s

22,000 chips each time you raise and take, and before you know it, your stack is

approaching the coveted 1 million chip mark.

Then, a funny thought occurs to you: having this particular dynamic at the

table may actually be better than bursting the bubble. In pure cash terms,

knocking out two more players from the tournament will return double your buy in

amount at the least. But in terms of chips, keeping the field at 29 players –

and out of the money – presents the best opportunity to build an even bigger

stack. And as we all know, tournament chips equate to cash on an escalating

level, so as you progress later in a tournament, having more chips can mean the

difference between a min cash or winning life changing money.

Suddenly, a short stacked player shoves all in from the hijack position and

the action folds around to you in the big blind. A look over at the other table

confirms that only 28 players remain, so this is your shot to burst the bubble

and ensure a cash. You peek down to see Ad 9d, certainly good enough to warrant

a call, and probably the better hand against a short shover.

But instead of calling to put the player at risk, you shake your head as if

it’s the 9 2 instead, and toss the cards into the muck. The short stacked player

lives to fight another day, and you go back to raising on the very next hand –

and many more after that – ravaging your fearful opponents for every last chip

before the money bubble finally does break.

Had you called and eliminated the shorty with ace high, you’d have added a

paltry 20,000 to your stack – or just two big blinds. But by folding, and

keeping them in the game for a few more orbits, you were able to use the raise

and take method to add another 120,000 or so without facing any serious fight.

Those extra chips prove to be quite useful too, and instead of the usual 8th

or 9th place exit you wind up with on deep runs, you go on to win the entire

tournament for your first big time score.

In this case, you’ve successfully applied an exploitative strategy, because

you recognized that deviating from the normal optimal strategy of eliminating

short players worked to increase your EV. Given a normal tournament scenario,

calling with a huge chip advantage to bust a short stacked player from the field

would be the proverbial no brainer. Here, however, savvy players are able to

intuitively realize that a more productive strategy exists, one which involves

the antithesis of standard poker strategy: ensuring an opponent’s survival.

### Big Stacks Avoiding One Another on the Bubble

Back to the bubble phase of a tournament, which seems to provide more

opportunities for GTO maneuvers, picture yourself playing a big stack of 525,000

at the 1,000/2,000 blind levels. The average stack at the moment sits at

175,000, and while you have more than seven players at the table, one actually

has you covered with a 600,000 stack.

The field has dwindled to 39 players and the final 36 will make the money.

You’ve been playing relatively snug of late, as has your fellow big stack,

when action folds around to you on the button. With Ah Qs in the hole, you’re

ready to roll with a standard opening raise, so you make it 4,200 to go. The

other big stack is on the small blind and next to act, and rather than keep the

pot small, he splashes three of the pink 5,000 chips into the middle for a three

bet to 15,000.

The big blind gets out of the way and you’re left to ponder, but the ace

queen is just too good of a hand to lay down to a little pressure, so you call

to see the flop come Ac 9s 2c. The big blind tosses out a continuation bet of

25,000, and as you reach for the calling chips, you stop and think for a second:

“The rest of the table is littered with shorter stacks, and I’ve only

invested 15,000 of my 525,000 so far. I like my hand of course, but it could

easily be beat by A K, so it’s not like I have the nuts. Against any other

player at the table, somebody I had covered, I’d roll the dice and go with a big

raise here… but not this guy. It’d be foolish to go broke now, not with the

money one bustout away, so I’ll toss this one away and let him have it.”

You fold the big hand and move on to the next, even though standard strategy

would suggest a flat call, or even a raise, might be in order. The issue here

was simple, as most players late in tournaments prefer to survive rather than

exploit fine edges. With the money right around the corner, playing big pots

against opponents who can eliminate you just isn’t a logical move.

From a game theory perspective, this example illustrates a suboptimal

strategy, because a purely GTO approach to flopping a big ace on a dry board

would be to call or raise often, while folding almost never. This suboptimal

strategy may sacrifice a certain level of EV in terms of the actual hand, but

depending on a player’s bankroll situation or personal finances, folding a big

hand against a big stacked opponent on the bubble is actually the correct play.

Technically speaking, “soft play” of this nature isn’t compatible with the

non cooperative nature of the game, but in Texas holdem circles, avoiding the

“risk of ruin” takes precedence in several crucial endgame scenarios. Big stacks

at the table late in tournaments often operate under an unspoken assumption,

taking turns bullying the smaller stacks, but seldom engaging in outright

aggression against one another.

And to take the game theory implications one step further, poker experts

generally agree that the optimal strategy as a big stack in this situation

should be based on exploitative play. If you know a fellow big stack is

practicing avoidance, you can push them around much more easily, and it’s in

your best interest to do so in an attempt to build your stack even bigger while

eliminating your primary handicap to pure aggression.

### Playing “Bad” Hands Against Exploitable Opponents

For the most part Texas holdem hand ranges can be played in relatively

straightforward manner. Everyone gets creative with funky suited connectors and

baby card hands of course, but at the lower stakes, playing a snug game which

incorporates premiums and top tier hands from early and middle position will

prove to be profitable.

## Poker Gto Definition List

But every poker game is a different animal entirely, consisting of unique

playing styles and personalities, along with constantly fluctuating variables

like stack size, positions, and indeed, hole cards. In certain situations, you

may find yourself expanding your range drastically, playing basically every hand

in an attempt to exploit your post flop advantages over a weaker opponent.

Every casino and card room has its resident drunk, so imagine yours has just

stopped by with a full rack of red $5 chips and a rye bourbon on the rocks in

hand. She sits down in your usual $2/$5 cash game, and before her $500 in chips

is even unracked, she’s stacked an unfortunate soul by going runner runner to a

straight. The inebriated gal’s cards? The lowly 2d 4c.

She flopped nothing but a deuce on the Kc 6s 2h flop, called a bet to see the

3d fall on the turn, and called an even bigger wager to find her 5d gin card on

the river. Just like she drew it up.

At this point, your radar is blaring alarm bells and you realize that an

opponent demonstrating an extremely exploitable strategy has just arrived on the

scene. Rather than stick to the usual script and play your usual range of high

cards and pocket pairs, you begin to enter as many pots as possible, intending

to connect with any sort of hand that can run down the lady’s loose play.

It takes an orbit or two, and you bleed a few chips along the way while she

continues to act as the table card rack, but eventually you call her opening

raise with the 10d 8d and catch a nice Jd 9c 2c flop. With an open ended

straight draw you call the woman’s continuation bet on the flop, catching a Qc

on the turn to make the nut straight. The woman suddenly slows down with a tap

of the table, checking it over to you.

You fire out a wager and she comes over the top with a big all in raise,

which you happily snap off with your nut straight. She shows the Qd 2h for a

ragged two pair, having flopped bottom pair and made two pair on the river. Your

straight holds through the river blank and you take a hand like 10 8, which you

never would’ve played otherwise against a player using a standard strategy, to

score a massive double up.

In this instance, you’ve used an exploitative strategy – one which deviates

from normal GTO strategy – to take advantage of unique game conditions. Against

most opponents, hands like 10 8 may not be the most profitable holding over the

long run, but here you correctly identified an opponent who would allow you to

take the low risk, high reward shot.

And even better? The lady’s propensity for aggression ensured that when the

right spot finally arrived, your big hand materialized into a massive payoff.

### Using Push / Fold Charts to Dictate Short Stack Play

One of the more difficult phases of any tournament involves reaching the

endgame with very little chips to work with.

## Gto Definition For Poker

The excitement of running deep is counterbalanced by the desperation of

needing a quick double up. In this spot, most recreational players, and quite a

few professionals, are plagued by the problem of patience.

For some players, they’re not patient enough, and the sight of any face card

is enough to warrant a reckless shove. For others, patience isn’t really a

virtue, because as they wait for the perfect hand with which to make their

stand, their stack dwindles to the point of irrelevance.

To help solve this dilemma, poker focused game theorists have crunched the

various probabilities based on hand strength relative to current big blind

volume. In doing so, they’ve created reliable “Push / Fold” charts that inform

players exactly which hands warrant a fold or an all in bet, based on how many

big blinds are currently in their possession. These charts function just like

the basic strategy charts used by blackjack players, providing clear and defined

guidelines on the optimal way to approach close situations.

Using a Push / Fold chart is an example of purely GTO play, because the

probabilities have been studied to reveal the exact dividing line between

positive and negative EV plays. When you use a Push / Fold chart to dictate your

decisions, you’ve effectively removed the human element from the game, letting

pure mathematics define the difference between the right and wrong move.

At one point Push / Fold charts were scoffed at by poker players, but today’s

generation of game theory cognizant players has realized that any strategic tool

which makes GTO play easier is one worth incorporating into their overall game.

## Essential Texts and Resources

As we mentioned earlier, the author of this page in no way, shape, or form

claims to be an expert in Texas holdem game theory. We can’t teach you the proof

behind the Nash Equilibrium, the exact formula for a “strategy space,” or

anything at all about the concept of “Condorcet winners.”

What we can do, however, is provide a comprehensive list of books, websites,

and other resources that specialize in both game theory as a field of study, and

its practical applications for poker’s most popular game. These resources were

written, or otherwise created, by experienced experts who have spent the long

hours in the classroom which are required to wield advanced game theory

knowledge.

With that said, everybody learns differently, so a dense textbook style

treatise on game theory may not work as well for you as it does for others.

Conversely, visual aids and interactive features are perfect for some students

who need a tangible grasp on abstractions, while more mathematically inclined

learners will have no need for the added clutter.

However you choose to learn about Texas holdem game theory though, the

following resources should provide a full fledged education on the topic, both

in a general sense and from the standpoint of GTO poker play:

### Poker and Texas Holdem Game Theory Reference

#### Books

- Poker Strategy: Winning with Game Theory | Nesmith C. Ankeny | 1981
- The Theory of Poker: A Professional Poker Player Teaches You How To

Think Like One | David Sklansky | 1999 - The Mathematics of Poker | Bill Chen and Jerrod Ankenman | 2006
- No Limit holdem: Theory and Practice | David Sklansky and Ed Miller |

2006 - The Mental Game of Poker: Proven Strategies for Improving Tilt Control,

Confidence, Motivation, Coping with Variance, and More | Jared Tendler M.S.

and Barry Carter | 2011 - Jonathan Little on Live No Limit Cash Games: The Theory | Jonathan

Little | 2014 - Poker’s 1%: The One Big Secret That Keeps Elite Players On Top | Ed

Miller | 2014 - Essential Poker Math: Fundamental No Limit holdem Mathematics You Need

To Know | Alton Hardin | 2015

#### Websites, Articles, and Other

- What Would Jesus Bet? | The New Yorker | 2009
- Poker Strategy With Reid Young: Game Theory vs. Pot Odds | CardPlayer |

Reid Young | - Game Theory Optimal Solutions and Poker: A Few Thoughts | Nikolai

Yakovenko | PokerNews | 2015 | - Got GTO? The Connection Between “A Beautiful Mind” and Perfect Poker |

Robert Wooley | PokerNews | 2015 | - Game Theory Optimal GTO Play for Poker Explained | John Anhalt | 2015 |
- Decision Theory and Nash Equilibrium in Texas holdem Poker | Harry

Copeland and Sam Leclerc | 2015 | - 3 Ways GTO Can Help Improve Your Live Game | Red Chip Poker
- Poker Game Theory – 4 Ways Poker Game Theory Can Improve Your Play | Sit

and Go Planet - Push / Fold Chart App | Float the Turn |
- Game Theory Simplified, and Why Fixed Strategies Fail | DoyleBrunson.com

### General Game Theory

#### Books

- Mathematics of Games and Gambling | Edward Packel | 1981
- The Compleat Strategyst: Being a Primer on the Theory of Games of

Strategy | J.D. Williams | 1986 - Prisoner’s Dilemma: John von Neumann, Game Theory, and the Puzzle of the

Bomb | William Poundstone | 1993 - Game Theory: A Nontechnical Introduction | Morton D. Davis | 1997
- The Art of Strategy: A Game Theorist’s Guide to Success in Business and

Life | Avinash K. Dixi and Barry J. Nalebuff | 2010 - Game Theory 101: The Complete Textbook | William Spaniel | 2011
- The Complete Idiot’s Guide to Game Theory | Edward C. Rosenthal Ph.D. |

2011 - The Joy of Game Theory: An Introduction to Strategic Thinking | Presh

Talwalkar | 2014 - Game Changer: Game Theory and the Art of Transforming Strategic

Situations | David McAdams | 2014

## Poker Gto Definition

#### Websites, Articles, and Other

## Conclusion

Texas holdem game theory is one of the subjects that scare off many players

before they give themselves a chance to learn about it and use it. If you didn’t

take the time to read the entire page, set aside a few minutes and study it.

## Poker Gto Definition Meaning

If you do, you’ll realize that game theory isn’t that hard and you can start

using it to improve your results while playing Texas holdem. The best players

use game theory whether they realize it or not, so why not learn more about it

and maximize your chances to win?