GTOPokerGTO Solver
Strategy8 min read

Evidence-First Exploit Framework for GTO Learning

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Evidence-First Exploit Framework for GTO Learning

Short Answer

Exploit should be conditioned, not guessed. Set repeatable triggers and only expand adjustment range in bounded windows.

Four trigger levels

Layer 1: no change before sample sufficiency. Layer 2: spot-specific deviation confirmed. Layer 3: two-week repetition checks. Layer 4: positive contribution and clear rollback conditions.

Risk controls

Cap max size changes, set minimum rollback attempts, and auto-rollback if target edges weaken. Exploit is temporary amplification, not permanent strategy replacement.

Execution checklist

  1. Write deviation hypothesis and counter-conditions.
  2. Use 20k+ hands before claiming proof.
  3. Use fail thresholds and revert when EV trend decays.
  4. Reassess weekly and keep exploit distance from GTO baseline small.

Practice On Site

Frequently Asked Questions

How should I set a sample minimum?
Use 2,000 hands as observation only, 2,000-5,000 for caution, and 20,000+ for permanent style changes.
What to do when exploit fails?
Rollback first. Then confirm trigger validity before checking whether your sample was mixed or corrupted.

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