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With the 2026 WSOP Main Event final table set to resume shortly, Advanced Poker Training has run one million computer simulations to project how the tournament might unfold. The project was led by Steve Blay, a Florida-based academic and software developer who previously used a similar, far smaller model to correctly forecast Qui Nguyen’s 2016 win.
This year’s simulation is dramatically more powerful, running 10,000 times more trials than the 2016 version thanks to advances in computing capacity. The system can reportedly simulate an entire WSOP Main Event final table three times per second, incorporating more than 40 configurable behavioral traits per player.
According to the results, chip leader Jumalon, who holds roughly 35% of the chips, won the simulated tournament over 40% of the time. Blay noted that this dominance stemmed largely from ICM pressure limiting how aggressively opponents could challenge him, though Jumalon still busted in ninth place in about 1% of simulated runs.
Not every player fared as well as their stack suggested. Hammoud underperformed his ICM expectation by nearly 5%, a dip Blay attributes partly to seating position, since Jumalon’s big stack sits just two seats to his left, complicating his blind-stealing opportunities.
Shaevel and Mueller emerged as the model’s standout overperformers, benefiting from experience and favorable table position. Mueller, a three-time bracelet winner and former professional hockey player, was singled out as a fan-favorite underdog.
Despite acknowledging Jumalon as the mathematical favorite, Blay said he personally is backing Mueller to defy the odds and win the title, citing his tournament experience and repeated strong showings across the simulations.
