GTOPokerGTO Solver
Strategy8 min read

Evidence-First Exploit Framework for GTO Learning

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Evidence-First Exploit Framework for GTO Learning
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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

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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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