GTO LAB Tournament Savagery
Duration: 29+ Hours
Format: Structured MTT System (Preflop / Postflop / ICM / Final Table)
Level: Advanced Tournament Players
GTO LAB TOURNAMENT SAVAGERY is a 29+ hour AI-structured tournament poker masterclass built around logical stage progression and ICM-based decision trees. The content follows a layered tournament architecture: early cEV foundations → mid-stage ICM transitions → bubble pressure → post-bubble leverage → final table execution.
Developed by Nick Petrangelo and Daniel Dvoress, this system teaches how risk premiums, payout ladders and stack asymmetry reshape preflop ranges, postflop mechanics and EV maximization. Over 10 hours are dedicated exclusively to final table play, making this one of the most comprehensive structured MTT breakdowns available.
This is not random theory. It is structured tournament decision modeling designed for repeatable deep runs.
COURSE CONTENT OVERVIEW
├─ 1-Intro (1 file)
├─ 2-Preflop (20 files)
├─ 3-Postflop (17 files)
├─ 4-Blind vs Blind (3 files)
└─ 5-Fun and Esoteric Spots (2 files)
SAMPLE: https://t.me/epgsamples/5
SAMPLE: https://rumble.com/v75ntfa-gto-lab-tournament-savagery-cheap.html
SAMPLE: https://ok.ru/video/11971049294481
SAMPLE: https://rutube.ru/video/2f5b86051d00bc199321672dd4d3bef7/
Structured Learning Framework
Stage 1 – Early Tournament (cEV Foundations)
- Inequal stack theory
- Range construction mechanics
- High-frequency postflop spots
- 3-bet and SRP dynamics
Stage 2 – Mid Stages (ICM Transition Layer)
- cEV to ICM adjustments
- Risk premium modeling
- Stack pressure redistribution
- Bubble factor misconceptions
Stage 3 – Bubble Environment (Maximum ICM Pressure)
- Big stack vs mid stack leverage
- Short stack survival thresholds
- Accurate preflop ranges under pressure
- Exploiting overfolding populations
Stage 4 – Post-Bubble & Near Final Table
- Resetting risk premiums
- Field compression dynamics
- Preflop and hand review breakdowns
Stage 5 – Final Table Execution Engine
- 9–6 handed stack modeling
- 5–3 handed short-handed adjustments
- Big stack aggression calibration
- Bluffing in tight ICM ranges
- Complex sizing and exploit nodes
Instructor Authority
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Nick Petrangelo
|
Daniel Dvoress
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