Dylan Linde

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About

Dylan Linde, known online as “ImaLucSac” on PokerStars and “mezcal” on GGPoker, is a GTO LAB coach and one of the most decorated tournament players in the world, with three WSOP bracelets and a track record of deep runs across online and live high-stakes events. He brings a distinctly practical coaching philosophy — less about memorising solver outputs, more about understanding when and how to deviate from GTO to maximise your edge against real opponents.

Dylan’s coaching at GTO LAB is built around exploitative thinking and how to turn theoretical understanding into profitable adjustments in practice. His teaching topics include:

• Exploitative play frameworks — a logical, systematic approach to deviating from GTO baseline, including his 10-part Exploitative Play series covering postflop, ICM, solver usage, live reads, bubble play, and final table strategy
• Population exploits and opponent modelling — how to identify common tendencies in tournament fields, put opponents in uncomfortable spots they are unlikely to have balanced ranges for, and turn break-even GTO plays into profitable exploits
• Bubble and pay-jump dynamics — adapting to suspicious flat calls, implementing reverse linear betting for overpairs, exploiting micro-stack dynamics, and navigating ICM-heavy decisions under pay-jump pressure
• Play and explain sessions — live multi-table online sessions with in-depth thought process commentary on attacking capped ranges, PKO adjustments, and balancing GTO with real-world reads
• BB defense and preflop adjustments — equity realisation, range coverage, and how marginal hands lose value in multi-way pots
• Soft field strategy — how to widen opens thoughtfully, exploit population errors without spewing, and spot when standard adjustments need rethinking in large-field events
• Study methodology — why great study starts with the right questions, how to uncover macro concepts that drive solver strategy, and how to apply them in-game without becoming solver-dependent

Dylan’s coaching style is direct, structured, and built for players who want to move beyond theory and start making better decisions in the games they actually play.