What does GTO mean in Poker?

by | Feb 11, 2021 | Content | 2 comments

What does GTO Mean in Poker?

A brief introduction to game theory and how to use it

By Brandon Wilson


A GTO, or game theory optimal, strategy cannot lose. But it is also not guaranteed to win. That alone is enough to confuse many poker newcomers! Fear not, however—DTO is here to help.

In this article, we’ll learn the terms Nash equilibrium, deviation, and indifference, and piece them together using a hand example to create a basic understanding of GTO poker.

Key GTO terms defined

A Nash equilibrium is “a set of strategies that would be stable if nobody has a unilateral incentive to deviate from their own strategy,” (Holt and Roth 2004). When any poker solver provides an output, this is what it is creating—a plan for each player which, if adhered to unequivocally, will force any deviation from its opponent to be costly.

A deviation can come in any size, from minor inaccuracies to massive blunders—and every poker player makes them. When a player deviates from the equilibrium unknowingly, it is often a mistake, born of misunderstanding the situation’s equilibrium. When a player deviates knowingly, however, they can be said to be “exploiting,” or abandoning their understanding of the equilibrium in belief that their assumption will yield them an even better expectation than the “GTO” play. In the first scenario, the player making the mistake had no “unilateral incentive” to take the action he chose. In the second, however, the player’s incentive was his opponent-specific assumption.

Indifference in poker is a point at which two or more actions for a specific holding have the exact same expectation. Have you ever found yourself distressed as your opponent piles in a large bet against your middling hand, unsure of whether to look him up? It’s likely that the expectation of folding and calling for your hand are very close, or in many cases, the same.

GTO in practice: hand example

To see these concepts in action, consider the following chip EV situation: with a 20 big-blind stack, you raise first in raise from the Lojack with AcJc, and your opponent on the Button calls. The flop reads 5s4s3c.

Should you check or bet? If you bet—what size?

Let’s familiarize with the basic equilibrium of this spot.

GTO Poker Hand Example

Figure 1. DTO splits its flop action 51% check to 49% bet.

In figure 1, DTO mixes between betting small and checking, employing each at almost exactly a 50% frequency. This choice tells us that checking and betting small (24% pot) are worth the exact same amount of the pot, or have the same EV, and thus AcJc can be said to be mathematically indifferent to these two options. In arriving at its mix, DTO (and every solver) seeks to maximize the EV of every hand in its range. Doing so does not require, as is commonly misconceived, any “sacrifices” —that is, making a suboptimal play with one holding in the range in order to increase the EV of another. Poker situations invariably fluctuate in complexity, but the framework of indifference applies in every spot, on every street of the game tree.

Exploitative play

While a GTO strategy will always win against a non-cooperative strategy, it is also true that GTO may not extract the maximum value from specific opponents. As such, cynics of theoretical poker often encourage playing a simpler, intuitive style that emphasizes exploiting their opponents’ tendencies. This involves using qualitative analyses, or “reads,” to conclude that one option categorically out-earns another (such as checking 100% of the time in the previous example). However, without a thorough comprehension of the equilibrium’s mechanics, these deviations, or “exploits,” are often rash, erroneous, and harshly subject to confirmation bias.

In conclusion, grasping basic GTO principles is crucial to progress in poker. While there is certainly still value in knowing how to “play the player,” mathematically precise game theory is the foundation from which most of today’s top players operate.



About the author

Brandon Wilson is an American poker player and writer. He earned his Journalism degree from Northwestern University’s Medill School of Journalism, and after spending three years in the field, found poker. He credits DTO as instrumental to his improvement and uses the tool regularly. Outside of the game, Brandon teaches yoga and serves as a mentor for high school students for the Daniel Murphy Scholarship Foundation.



  1. Marc T.

    Great article! Looking forward for more articles like this ?

  2. Bart

    Nice post 🙂

    Does GTO include knowing how to “play the player,” in terms of opponent modeling? There are so many different GTO descriptions online that I am getting lost 🙂


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