The philosophy of PioSolver: “Game trees are like pieces of art”

Whether you like solvers or not, your opponents are using them every day to improve. The average poker player today is better than they have ever been, and tools like PioSolver are a major reason why. Ignore solver work entirely and you risk falling behind.

That does not mean you need to run your own sims to compete. Solver-approved preflop charts and coaching content can get you most of the way there. But if you are willing to put in the work with PioSolver yourself, the depth of understanding you gain is difficult to replicate any other way.

Here is how to approach PioSolver as a learning tool, with practical advice from BBZ cash game coach Wey “CRAIbaby” Xie on keeping your study manageable and productive.

Why Use PioSolver?

“I personally like to run sims because I am fascinated by the game at a fundamental level,” says Xie. “This might sound extreme to some extent, but you can perceive a really nice game tree like it is a piece of art. You can investigate them and be surprised by what the game has to offer.”

The goal with PioSolver is to find equilibrium solutions, meaning the game theory optimal (GTO) way to play a particular spot. This assumes your opponent is also playing optimally, which is rarely true in practice. “In higher stakes games we are going to assume that our opponents are playing very well,” says Xie. “But for the most part, this is going to be unrealistic. Your opponents are going to be making a lot of mistakes, even at higher stakes.”

That is actually the point. When you understand what the optimal strategy looks like, you can start to see where your opponents deviate from it and exploit those deviations. “Just try to understand why this kind of strategy is optimal,” Xie says. “Then we can start to understand how the game works and gain an intuition for how ranges and sizes affect what optimal play looks like.”

According to Xie, if you repeat this approach enough: “At some point, it is going to feel like you have a little PioSolver computer in your mind.”

Start with Restricted Bet Sizes

One of the biggest mistakes new solver users make is trying to include too many bet sizes in their sims. The resulting game trees are enormous, difficult to interpret, and overwhelming to study.

Xie recommends starting simple. “It might be useful to only play a two-size strategy, where you only have a half-pot bet and a pot-size bet, or 33%-pot and 75% pot, for example,” he says. “Then over time, you can expand your sizing pool to include overbets.”

This approach simplifies the game tree, making it easier to follow while still teaching you how to play an optimal strategy with the sizes available. “You will lose some expected value compared to having more sizing options, but this will not be too important as most of your value is going to be coming from your opponents making mistakes anyway,” says Xie.

The tradeoff is worth it. “You forgo a little EV, but you will never capture it anyway if you do not understand how to play the game.”

Expect to Re-Run Your Sims

The downside of starting with restricted sizes is that you will eventually need to run more sims as your understanding deepens. But Xie frames this as inevitable regardless of how you start.

“Rest assured, you are going to have to do that anyway as your understanding of the game increases,” he says. “Even I find myself correcting some of my sims every now and then. It is just part of the learning process.”

As you get more comfortable with the software, you can experiment with additional bet sizes, different board textures, and more complex game trees. Each iteration builds on what you learned before. The key is not to try to solve the entire game on day one.

Building Intuition, Not Memorizing Outputs

The real value of solver work is not memorizing specific frequencies for specific spots. It is building an intuition for why certain strategies are optimal so that you can apply that understanding to new situations you have never studied.

When you run a sim and see that PioSolver wants to check-raise a certain board texture at a high frequency, the question to ask is not “what percentage do I check-raise here?” The question is “why does this board favor the check-raiser’s range?” Once you understand the why, you can apply that logic to similar boards without needing to have run a sim on each one.

This is what separates players who use solvers effectively from those who just memorize outputs. Memorized frequencies break down the moment a situation changes slightly. Understanding the underlying logic transfers to every hand you play.