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Integration of Rough vs Smooth Betting Tells into GTO Framework (MTT)

Bluffing · updated 2026-03-08

What the "Smooth/Rough" Tell Actually Measures

How to Weight the Tell: Bayesian Layer on Top of GTO

  1. Start with a prior (GTO/pool-based frequencies).
  2. Assign the tell a likelihood ratio (LR) — how much it shifts us toward value or bluff for that opponent type.
  3. Update the decision (call/fold/raise) based on pot odds and expected frequencies.

Quick Template for River Decisions

Practice: Grade LRs for your pool based on notes. Start with soft values (0.7 / 1.3) and adjust by showdown data.

Exploits by Opponent Type

Recreational Player

Passive Regular

Active Regular (Crushers)

Stack and ICM Adjustments (MTT Specific)

Street-by-Street Adjustments

Flop

Turn

River

Quick River Decision Algorithm

  1. Compute pot odds.
  2. Identify opponent type (rec / passive / active reg).
  3. Assign LR for tell (softly).
  4. Check blockers (nut flush/straight blockers > weak ones).
  5. Under ICM pressure when covered ⇒ reduce hero-call frequency on "rough".
  6. Decide: call / fold / bluff-raise (raise only with strong blockers and history).

Working on Your Own "Opacity"

Practice Tasks

If you want, share a specific MTT hand (stack, positions, payout, action history, sizings, and observed "smooth/rough"). I will provide exact ranges, sizings, and EV comparison accounting for ICM.

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