Daniel Dvoress

Widely respected as one of the most formidable and analytical players in the game, Daniel Dvoress is a Canadian professional who has dominated both live and online high-stakes tournaments for over a decade. Known online as “Oxota,” his approach is rooted in deep theoretical understanding and precise execution under pressure.

Originally from the Soviet Union, Daniel emigrated to Canada at age 8 and showed an early aptitude for mathematics that would later define his poker career. While he maintains a famously private persona and is “Vegas-averse,” preferring to stay out of the spotlight, his expertise is among the most sought-after in the world.

Before co-founding GTO LAB with Jonathan Jaffe and Nick Petrangelo, he was one of the top-rated and most popular coaches on several other training sites, solidifying his reputation as not just a world-class player, but a world-class educator. His live tournament earnings now sit at $45,013,408, with consistent six- and seven-figure scores across Super High Roller, Triton, and WSOP events. He is widely respected for his ability to mix formats and perform under big-buy-in pressure.

His breakout large score came when he won the $250,000 Super High Roller Bowl Bahamas for $4,080,000. Since then he has added major results including a bracelet at the WSOPE €25,000 GGMillion$ for €600,000. He has also one Triton Titles in other variants, winning the $50k PLO in Monte Carlo, and $20k Short Deck event in Cyprus. He finished fourth in the $500,000 Triton Million Invitational (WSOP Paradise 2024) for $4,390,000 and has multiple other final tables to his name.

Dvoress’s practical study method focuses on linking solver outputs to live adjustments. His teaching emphasizes ICM awareness, pressure mapping, and exploitable tendencies in high-roller pools. Sessions center on why a solver line exists, when table dynamics suggest deviation, and how to execute under time pressure.

Ready to Level Up Your Game?
Study with Daniel at GTO LAB and learn the same frameworks he uses to make decisions on the biggest stages.