How the Strategy Is Built

Meta Scan

Digging Deep into the Meta

We analyze massive hand histories per site and limit to uncover how the population actually plays.

Game Tree

Modeling the Real Game Tree

From the meta trends, we construct full decision trees that replicate how the player pool actually plays each spot.

Highest EV Line

We Hit the Highest-EV Line

Each action’s EV is computed based on current and future leaks in the pool, exposing the highest-value path in the spot.

Beating GTO with Data-Driven Exploits

Why GTO Limits Your Winrate

  • Assumes your opponents play GTO — they don't
  • Gives up EV in spots just to stay balanced overall
  • Bluffs and bluff-catchers just for balance — even when they're losing money vs the meta
  • Too complex to apply — impossible to mix ranges like this in real games
  • Even with nodelocking, the tree assumes GTO beyond that node — still far from max-EV

Exploit and crush

  • Always targets the most profitable line by punishing meta leaks
  • GTOKiller lets you choose site and stakes to give you meta-specific solutions
  • Punishes common pool leaks — overfolds, spewy bluffs, and unbalanced sizings
  • No assumptions about villain's range — just massive meta-driven decisions
  • Crushes even in high-rake games where GTO just doesn't win