Deputy Editor
Popular poker solver GTO Wizard has added player profiles to its database, enabling players to build opponent-specific strategies.
“Profiles enable you to model opponents with persistent leaks and exploitable tendencies,” the company wrote in its explainer. “You can apply a profile to any solvable spot in GTO Wizard AI. Want to beat a calling station, shut down a maniac, or navigate a nit that suddenly shows strength? Simply attach a profile, and study the best response.”
The profiles are meant to produce optimal counter-strategies for one street, as GTO Wizard doesn’t have multi-street functionality for the mechanic yet.
GTO Wizard’s team has clearly been hard at work lately, as the player profiles are the second major addition to the platform in just a few months. In August, the team added post-flop multi-way solutions. Unfortunately, all these new features have inherent limitations, which is partially why we’re only now seeing solver developers attacking these problems, now that the low-hanging fruit has been collected.
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Why Opponent Exploits Matter for GTO Wizard
If GTO Wizard can build a theoretically perfect strategy, why do the player profiles matter? That answer is that the “game theoretically optimal” equilibrium strategy is only perfect against another opponent playing an equilibrium strategy. The GTO solution is unexploitable by any opponent, but it is not typically the most profitable approach against an off-equilibrium opponent.
A player deviating from equilibrium inevitably has weaknesses that can be exploited. While an equilibrium strategy will make money in this case, it won’t make the most money possible.
Since no real-life opponents will play a perfect equilibrium strategy, maximizing profit means building an exploitative strategy tailored to the particular opponent’s deviations. But there’s the catch: an exploitative strategy is also a deviation from equilibrium. Any time a player is trying to exploit their opponent, they become exploitable in turn. So, this new feature is one to use with caution.
“Profiles are designed to bridge the gap between pure theory and reality,” the GTO wizard team wrote. “This is the first time you can set up a simulation against a specific player type and see the mathematically sound counter-strategy emerge.”
What Exploitative Strategies Look Like
To give a simple example of how this works, imagine you’re facing an opponent on the river with a pot-sized bet remaining. A standard solver strategy will mandate that you have a 2-1 ratio of value bets to bluffs in your range. That’s the ratio that makes you unexploitable, because the opponent is getting 2-1 to call. When those ratios line up, the opponent’s profit/loss by calling is statistically zero, which makes them indifferent between calling and folding.
By the same token, the opponent should be calling half the time, because that’s what makes you indifferent to bluffing a bad hand or checking it down and surrendering.
However, if you know the opponent will only call that river bet with the top 10% of their range, the exploitative adjustment is obvious. You should stop making value bets except with the nuts, while turning any hand you think is less than 80% to win at showdown into a bluff. By betting all your weak hands and none of your moderately strong ones, you’ve successfully exploited the opponent’s nitty strategy, which is the root of the GTO Wizard update.
The caveat is that if you’re wrong about the opponent’s tendencies, then your shift away from unexploitable strategy may backfire. If they start calling more than half of the time, you are suddenly being exploited rather than exploiting.
An Archetype-Based Approach to Opponent Profiling
Naturally, real-world opponents’ deviations usually won’t be as extreme, and most poker situations aren’t as mathematically clear-cut as our example. Most strategic adjustments will contain more nuance than simply “never value-bet, always bluff.” And like all solver strategies, players are better off taking away general ideas than trying to copy them exactly.
GTO Wizard’s current implementation doesn’t allow detailed modeling. Instead, you can solve for strategies against a limited set of familiar archetypes:
- Fish: calls too much, “donk bets” too much, doesn’t raise or fold enough
- Calling Station: defaults to checking and calling in many situations
- Glass Cannon: responds to passivity with aggression, but folds too much when the tables are turned
- Maniac: bets and raises too much, hates to fold
- Nit: checks and folds too much, doesn’t play aggressively or make hero calls
- Tight-aggressive regular: reasonable but slightly too conservative
- Loose-aggressive regular: reasonable but slightly too aggressive
Case Study: Should You C-Bet Against a Maniac?
PokerScout tested the profiles out a bit. In many situations, the result of applying a profile was less dramatic than you might expect. For example, a betting frequency might only change by a few percentage points.
There were some cases, however, when applying a profile radically altered the solver’s approach. Here’s one example.
This is the GTO solution for an early-position raiser 50 big blinds deep, when the button calls and the flop is A-6-4 with two suits:
In this chart, green represents the optimal frequency of checking, and red is the optimal frequency of betting. Black represents the percentage of the time that an early position GTO player would have folded preflop and thus won’t be here at all.
As you can see, the solver recommends checking most hands most of the time. Nonetheless, it also tells us we should bet medium-strength hands like 7-7, A-K, and K-6 at least some of the time, for value and protection. It also mixes in a few strong hands like A-6 and 6-6 for balance, along with rare bluffs with offsuit K-Q or Q-J.
If we change the opponent to a maniac, however, the red all but disappears from the chart:
Understanding that the opponent will rarely fold and might raise, the solver wants to check almost every time, except occasionally with strong-but-vulnerable hands like top pair-top kicker, two pair, and bottom set. All the middling hands that previously wanted to bet for protection can now happily check-call. The danger of checking, ordinarily, is that an opponent with a drawing hand could take a free card. Against a maniac who can reliably be expected to semibluff any kind of draw, that risk disappears.
