The unseen edge: Why exploitability matters
September 9, 2025
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The unseen edge: Why exploitability matters
Most PLO players trust convergence as their quality metric. They run simulations, watch them converge, and assume the output is optimal. This makes sense on the surface: convergence suggests the solver has found a stable solution.
But convergence only tells you the solver stopped improving. It doesn’t tell you if the solution is any good. This creates a fundamental problem in PLO solving. You could be using a perfectly “converged” solution that’s systematically exploitable. The solver reached a stopping point, but that point might be far from optimal. Without a way to measure solution quality directly, you’re flying blind.
Building different tools
We built Flop Hero Precision models because we wanted to solve the measurement problem directly. Rather than improving existing approaches, we started from scratch with a different philosophy. The core insight was that PLO players need different tools for different situations. Sometimes you need broad coverage for exploration. Sometimes you need maximum precision with guarantees. No single approach optimizes for both.
Our Expand models handle the exploration case. They work like traditional solvers, using convergence metrics and designed for rapid analysis across many situations. They’re built for speed and coverage when you need to explore new strategic territory or get quick reads on unfamiliar spots.
Our Precision models are engineered differently. They’re designed for accuracy with verified quality guarantees. When we specify a Precision solution has less than 0.5% exploitability, that’s a mathematical statement: even a perfect opponent who knows your entire strategy cannot extract more than 0.5% of the pot per hand.
This isn’t a marketing claim
It’s a measurable guarantee backed by direct calculation.
The measurement problem
The PLO solver market has been built around computational metrics rather than strategic ones. Solvers report convergence rates, iteration counts, and volatility settings. These numbers tell you about the solving process, not the quality of the result.
It’s like judging software by how long it took to compile rather than whether it works correctly. The process metrics might look perfect while the output has serious flaws.
This happens because PLO’s complexity forces solvers to use shortcuts, which in game theory is called abstractions. With 270,000 possible starting hands and massive decision trees, some simplification is unavoidable. But every abstractions introduces potential weaknesses (we call it exploitability). The question is whether you can measure and control those exploitability.
Rethinking EV calculation
We also reconsidered how EV should work in solver output. Traditional approaches calculate EV as a snapshot of the current strategy state. This produces an EV result that align with current decisions but don’t give you much insight into solution quality.
In Flophero Precision, we calculate EV as a predictor of quality issues. Instead making snapshots every few iterations, we calculate it at the end of the training time.
When you see EV discrepancies in our Precision solutions, you’re seeing the small amount of strategic imperfection that remains. That final 0.5% we haven’t eliminated. The misalignments between actions and EV directly reflect the exploitability still present in the solution.
Complete strategic coverage
Our Precision approach also addresses coverage limitations in existing solvers. We provide complete flop coverage with precalculated turns and real-time river solutions. We’re currently at around 225,000 postflop simulations, targeting 350,000 by early September. Largest competitors sit in around 35,000 simulations.
225,000
Postflop simulations
350,000
By early September
35,000
Largest Competitor
Most competitors provide convergence metrics from a single modeling approach. They can tell you their solver converged but not how good the converged solution actually is. The computational process completed successfully.
The combination of verified quality guarantees, complete coverage, and predictive EV calculation creates something fundamentally different. You get solutions with quality guarantees, not just computational completion certificates.
The complexity challenge ahead
The next major frontier is 5-card and 6-card PLO. These variants present exponentially greater complexity, roughly 8 times and 64 times more complex than 4-card PLO, respectively. The computational requirements scale dramatically, and the technical challenges become much more difficult.
We’re actively researching but we maintain realistic timelines. We won’t release Precision models for 5-card or 6-card PLO until we can meet the same quality standards we’ve established for 4-card.
The evolution of PLO solving is about building different models with better measurement, clearer guarantees, and tools that match the sophistication required by serious players.
Building the future!
We’re building toward that future, one verified solution at a time.
