Squid poker strategy: how progressive bounties change the game

Squid, PKO, Stand-Up — the vocabulary

• Squid / PKO / Progressive Knockout — bounties accumulate. Eliminate a player, take a share of their bounty, and your own bounty rises. Later eliminations are worth more than early ones.
• Stand-Up — bounty markers are assigned up front rather than accumulating, with capped reward logic. Different maths, same underlying insight: winning a pot and eliminating a player are separately valuable.
• Chip-EV — the standard solver model, where the only thing at stake is the pot. Correct in a cash game, wrong here.

Different rooms and communities use different names for the same structure. IkaSolver calls it Squid mode; if you search for PKO strategy, you're searching for the same thing.

Why chip-EV solutions mislead you

Take a marginal call for your tournament life against a short stack. In chip-EV, you fold — you're a small dog and the pot doesn't compensate. Add a bounty and the same call has a second payoff: eliminate them and you bank their bounty and grow your own for every future confrontation. That extra equity can flip a clear fold into a clear call.

The effect is not uniform. It scales with the bounty relative to the pot, with how covered you are, with how many players are still live, and — in progressive formats — with how much your own bounty stands to grow. That's four interacting variables. Adjusting for them by feel is guesswork; this is exactly the kind of problem solvers exist for.

Five things that shift in bounty games

1. Calling ranges widen against covered short stacks. Every hand that eliminates them carries bounty equity on top of pot equity.
2. Big stacks get more aggressive against covered players. You can only collect a bounty from someone you cover — so the same shove is worth more to the chip leader than to a short stack.
3. Short stacks with big bounties get isolated. You want them heads-up against you, not in a multiway pot where three players share the chance.
4. Multiway pots dilute bounty equity. Every extra player is another claimant on the same bounty — which is why multiway support matters more here than in chip-EV.
5. Multiplier tiers create thresholds. Where a format pays a multiplied bounty past a threshold, the correct strategy changes sharply around it — not something you can eyeball.

Solving Squid spots properly

To get real answers you need a solver that models the payoff structure directly, not one that solves chip-EV and lets you fudge. IkaSolver's bounty mode takes bounty price, first-round amount, total markers, split-payment behaviour and multiplier tiers as inputs, then solves the actual game — up to 9 players — and reports the win-impact matrix showing what each player's elimination is worth to every other.

The full configuration reference is in the docs: Bounty Mode →

A practical study routine

1. Pick a real structure you play — the actual bounty size and multiplier rules from a tournament you enter regularly.
2. Build the tree at a stack depth that matters (typically 15–30bb, where bounty pressure is sharpest).
3. Solve it, then read the win-impact matrix before the strategies. Knowing who your elimination is worth most to reframes everything downstream.
4. Load the solve into the trainer and play the spot 50 times. Filter to the hand classes you're least sure about.
5. Change one variable — bounty size, or player count — re-solve, and compare. The direction of the change is the transferable lesson.

Common mistakes

• Treating every bounty spot the same. A small bounty barely moves the needle; a large one rewrites the range. Solve, don't assume.
• Widening against players you don't cover. You can't collect a bounty you can't win. This is the single most common leak.
• Ignoring your own bounty's growth. In progressive formats your future bounty is part of the current decision's value.
• Studying heads-up solutions for multiway spots. Bounty equity divides across the field. Two-player solutions systematically overvalue aggression multiway.

Frequently asked questions