GTO (part 1)

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sxm59

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I will use the following example in several posts to explain a few GTO concepts and their usefulness and limitations.

Example:

The river is a blank. Villain has air with probability 50% (say, he missed a flush) or a strong hand with probability 50% (say, he flopped a set). Hero has only a bluff catcher (say, she flopped top pair). [Technical note: I will assume that both players are rational, selfish, and risk-neutral. Furthermore, everything about this example is common knowledge of the two players. In future posts, I may discuss how the equilibrium changes if these assumptions are not satisfied.]

For simplicity, suppose there is $30 in the pot, Villain is first to act and has $10 left in his stack. Hero has a much larger stack. Suppose Villain will either check or shove (that is, bet all his remaining $10).

The Perfect Bayesian Nash Equilibrium strategies are as follows:

1) When Villain has a strong hand, he shoves; when he has air, he shoves 25% of the time and checks 75% of the time.

2) When Villain checks, Hero checks; when Villain shoves, Hero believes that Villain has air with probability 20%, and Hero calls 75% of the time and folds 25% of the time.

In my next post, I will prove that the above strategies and beliefs are the unique (Perfect Bayesian Nash) equilibrium. That will be a bit technical. Here, I will do something more fun. I will try to explain how the equilibrium changes if the pot is larger than $30.

There are two key facts to keep in mind. First, your opponent's action conveys information. In the above example, initially (just before Villain's action) Hero correctly believes that Villain has air 50% of the time. However, because in equilibrium Villain shoves less often when he has air than when he has a strong hand, as soon as Hero sees Villain shoving, Hero understands that it is now less likely (than before seeing the shove) that Villain has air. In the example, that likelihood or probability decreases from 50% to 20% because Villain only shoves 25% of the time when he has air (versus 100% of the time when he has a strong hand).

Second, a rational player will randomize between two actions--say, between calling and folding--only if he or she is indifferent between the two actions, that is, only if the two actions have the same expected value ("EV"). Indeed, if calling has a lower EV than folding (in a given particular spot), why would a rational player call with any positive probability? If you prefer beer over wine, why would you flip a coin to decide what to drink?

Now, consider again the above example but suppose that the pot is $40 instead of $30. If Villain does not change his strategy, then Hero will prefer to call Villain's shove all the time (since when Villain has a strong hand, Hero still loses the same $10 as before, but she now wins $50 instead of $40 when Villain has air). But if Hero calls all the time, then Villain should change his strategy: he should not shove when he has air. So, the equilibrium strategies must be different. Specifically, to prevent Hero from calling all the time and to keep her on the fence between calling and folding, Villain must bluff-shove less often (16.7% of the time instead of 25%) when the pot is larger ($40 instead of $30). And to prevent Villain from shoving all the time and keep him on the fence between shoving and checking, Hero must call more often (80% of the time instead of 75%) when the initial pot is larger ($40 instead of $30).

To be continued...
 
Navin Sarabjeet

Navin Sarabjeet

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I will use the following example in several posts to explain a few GTO concepts and their usefulness and limitations.

Example:

The river is a blank. Villain has air with probability 50% (say, he missed a flush) or a strong hand with probability 50% (say, he flopped a set). Hero has only a bluff catcher (say, she flopped top pair). [Technical note: I will assume that both players are rational, selfish, and risk-neutral. Furthermore, everything about this example is common knowledge of the two players. In future posts, I may discuss how the equilibrium changes if these assumptions are not satisfied.]

For simplicity, suppose there is $30 in the pot, Villain is first to act and has $10 left in his stack. Hero has a much larger stack. Suppose Villain will either check or shove (that is, bet all his remaining $10).

The Perfect Bayesian Nash Equilibrium strategies are as follows:

1) When Villain has a strong hand, he shoves; when he has air, he shoves 25% of the time and checks 75% of the time.

2) When Villain checks, Hero checks; when Villain shoves, Hero believes that Villain has air with probability 20%, and Hero calls 75% of the time and folds 25% of the time.

In my next post, I will prove that the above strategies and beliefs are the unique (Perfect Bayesian Nash) equilibrium. That will be a bit technical. Here, I will do something more fun. I will try to explain how the equilibrium changes if the pot is larger than $30.

There are two key facts to keep in mind. First, your opponent's action conveys information. In the above example, initially (just before Villain's action) Hero correctly believes that Villain has air 50% of the time. However, because in equilibrium Villain shoves less often when he has air than when he has a strong hand, as soon as Hero sees Villain shoving, Hero understands that it is now less likely (than before seeing the shove) that Villain has air. In the example, that likelihood or probability decreases from 50% to 20% because Villain only shoves 25% of the time when he has air (versus 100% of the time when he has a strong hand).

Second, a rational player will randomize between two actions--say, between calling and folding--only if he or she is indifferent between the two actions, that is, only if the two actions have the same expected value ("EV"). Indeed, if calling has a lower EV than folding (in a given particular spot), why would a rational player call with any positive probability? If you prefer beer over wine, why would you flip a coin to decide what to drink?

Now, consider again the above example but suppose that the pot is $40 instead of $30. If Villain does not change his strategy, then Hero will prefer to call Villain's shove all the time (since when Villain has a strong hand, Hero still loses the same $10 as before, but she now wins $50 instead of $40 when Villain has air). But if Hero calls all the time, then Villain should change his strategy: he should not shove when he has air. So, the equilibrium strategies must be different. Specifically, to prevent Hero from calling all the time and to keep her on the fence between calling and folding, Villain must bluff-shove less often (16.7% of the time instead of 25%) when the pot is larger ($40 instead of $30). And to prevent Villain from shoving all the time and keep him on the fence between shoving and checking, Hero must call more often (80% of the time instead of 75%) when the initial pot is larger ($40 instead of $30).

To be continued...

So in the example of the $30 pot.
When villain shoves river, hero has to put $10 to get $50 back right?
So hero has to be right here 20% of the time to make it a profitable call on the long run.
So thats why he should be calling 80% of the time if i am not mistaken.

Just checking if i am understanding this:)
 
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So in the example of the $30 pot.
When villain shoves river, hero has to put $10 to get $50 back right?
So hero has to be right here 20% of the time to make it a profitable call on the long run.
So thats why he should be calling 80% of the time if i am not mistaken.

Just checking if i am understanding this:)

Yes, in the example of the $30 pot, Hero has to be right 20% of the time to make it a profitable call. But Hero should be calling 75% of the time (not 80%), so you are mistaken.

If Hero were calling 80% of the time, as you are suggesting, then Villain would not shove when he has air, which in turn implies that Hero should not call, contradicting that calling 80% of the time is GTO. (Villain would not shove when he has air because he is putting $10 to get $40, so his bluff needs to work 25% of the time. That is why Hero should be calling 75% of the time.)
 
Zapahlohotrona

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It is very interesting and what limits do you play? Before nl200, almost no one even uses the basics of GTO, and they are not needed in principle. Playing on GTO is not a magic pill that always allows you to play a plus.Playing on GTO is a trivial software calculation of situations when a GTO calculator balances your bluff range and value from preflop to river as much as possible in relation to your opponent.
 
Navin Sarabjeet

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Yes, in the example of the $30 pot, Hero has to be right 20% of the time to make it a profitable call. But Hero should be calling 75% of the time (not 80%), so you are mistaken.

If Hero were calling 80% of the time, as you are suggesting, then Villain would not shove when he has air, which in turn implies that Hero should not call, contradicting that calling 80% of the time is GTO. (Villain would not shove when he has air because he is putting $10 to get $40, so his bluff needs to work 25% of the time. That is why Hero should be calling 75% of the time.)


Ah ok.
I just calculated it from hero's point of vieuw, 100% - 20%(calling range) = 80%
But as you said: I have to take it from villains point of vieuw, as he is bluffing 25% then the remaining 75% is for a call from hero.

But one question here.
If Villain is bluffshoving only 25% of the time and Hero is calling his shoving range 75% of the time, will that not give Hero a losing call on the long run, because he is calling his value hands more of the time?
 
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It is very interesting and what limits do you play? Before nl200, almost no one even uses the basics of GTO, and they are not needed in principle. Playing on GTO is not a magic pill that always allows you to play a plus.Playing on GTO is a trivial software calculation of situations when a GTO calculator balances your bluff range and value from preflop to river as much as possible in relation to your opponent.


I am not trying to "sell" or recommend playing GTO to anyone. In my opinion, it is impossible to play GTO poker because it is impossible to find the GTO equilibrium strategies except in very simple situations. Solvers are "black boxes" that come up with ranges based on principles, assumptions, or Monte Carlo experiments, but they are not GTO equilibrium ranges because they do not (and cannot) solve for the GTO equilibrium in the vast majority of situations. Even if they could, and when they can, playing the GTO strategy may not be the most profitable strategy depending on the opponent you face.

However, I am a game theorist and I enjoy solving for the GTO equilibrium in very simple situations where it can be calculated. I think it is interesting in its own right, and potentially useful as it can provide some guidance for how to adjust one's play to different situations.

Some concepts, like for example Minimum Defense Frequency, are useful to many styles of play (not only to GTO-ish styles).

Finally, my post, and other future posts on GTO, are intended for members who are interested in learning the mechanics of GTO. I probably should have stated that lound and clear from the get go.
 
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Ah ok.
I just calculated it from hero's point of vieuw, 100% - 20%(calling range) = 80%
But as you said: I have to take it from villains point of vieuw, as he is bluffing 25% then the remaining 75% is for a call from hero.

But one question here.
If Villain is bluffshoving only 25% of the time and Hero is calling his shoving range 75% of the time, will that not give Hero a losing call on the long run, because he is calling his value hands more of the time?


First, in the example with a $30 pot, Villain is bluff-shoving 25% of the time and Hero is calling 75% of the time, but the fact that these frequencies add up to 100% is just a coincidence. That can be seen from the $40 pot example where Villain is bluff-shoving 16.7% of the time and Hero is calling 80% of the time.

Regarding your question, in the example with a $30 pot, where Villain is bluff-shoving 25% of the time and Hero is calling 75% of the time, Hero is not losing money by calling or else she would fold. And she is not making money by calling either or else she would call 100% of the time. So, she gets exactly zero from calling (and zero from folding). Indeed, 25% of the time Villain has air and Hero wins the $30 pot, and 75% of the time Hero loses the $10 call: (0.25 x $30) + (0.75 × (-$10)) = 0.

That was a good question!
 
Navin Sarabjeet

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First, in the example with a $30 pot, Villain is bluff-shoving 25% of the time and Hero is calling 75% of the time, but the fact that these frequencies add up to 100% is just a coincidence. That can be seen from the $40 pot example where Villain is bluff-shoving 16.7% of the time and Hero is calling 80% of the time.

Regarding your question, in the example with a $30 pot, where Villain is bluff-shoving 25% of the time and Hero is calling 75% of the time, Hero is not losing money by calling or else she would fold. And she is not making money by calling either or else she would call 100% of the time. So, she gets exactly zero from calling (and zero from folding). Indeed, 25% of the time Villain has air and Hero wins the $30 pot, and 75% of the time Hero loses the $10 call: (0.25 x $30) + (0.75 × (-$10)) = 0.

That was a good question!

If it is calculated in this way then its perfectly correct:)

So everything is not 100% based (it is at least close to 100%) = understood:icon_thum

Waiting eagerly for some more examples, i am very hungry for learning:D
 
BelFish

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However, I am a game theorist and I enjoy solving for the GTO equilibrium in very simple situations where it can be calculated. I think it is interesting in its own right, and potentially useful as it can provide some guidance for how to adjust one's play to different situations.

I too love all sorts of calculations! Later i will give you a link to a topic with a rather interesting and complex example.

In the meantime, you can watch one of my old topics with an interesting calculation in combinatorics. Maybe you will like it too:

https://www.cardschat.com/forum/learning-poker-57/probability-ace-best-kicker-depending-number-490000/

The probability of the ace with the best kicker depending on the number of opponents.
 
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BelFish

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Strange, i copy the link, paste, but it does not open...
 
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