Collusion Patterns: How to Spot Online Poker Team Play

Online poker is built on one core assumption: every seat is playing for itself. The moment two (or more) players secretly share information or coordinate decisions, the game stops being poker and turns into a rigged puzzle you can’t solve from your chair.

Collusion—especially “team play”—isn’t always loud and obvious. The strongest groups don’t dump stacks every orbit and cackle in the chat. They blend in. They win smaller edges repeatedly. And they often do it in ways that feel like “bad luck” until you zoom out and look at patterns.

This article is a practical, poker-player-friendly guide to spotting collusion patterns in online games—cash, tournaments, and fast-fold formats—using the exact clues that show up in hand histories, HUD stats, and table behavior. You’ll also learn what doesn’t mean collusion (so you don’t waste mental energy accusing every nit), plus what to do if you suspect something is real.

What “Team Play” Collusion Looks Like in 2026 Online Poker

The classic idea of collusion is chip-dumping: Player A deliberately loses chips to Player B. That still happens, but modern team play is often more subtle and more profitable long-term:

Soft play: avoiding aggression against each other; checking down; refusing to value bet thinly; passing on profitable bluffs that would pressure the partner.
Information sharing: telling a teammate what you folded, what you held, or what a third player showed down.
Squeeze protection & pot control: teammates entering pots in ways that isolate a target and discourage action from others.
ICM manipulation (tournaments): strange fold patterns late, “convenient” all-ins, or passivity between partners to ladder together.
Seat/format abuse: queuing together, table selecting together, or repeatedly appearing in the same player pools in ways that feel statistically “too consistent.”

Important note: Playing “similar styles” isn’t collusion. Two regs being tight, 3-betting a lot, and avoiding marginal spots can be totally normal. Collusion is about coordinated decisions or shared intent, and the only reliable way to identify it is through repeated, consistent patterns across many hands.

The Most Common Collusion Patterns (And the Poker Logic Behind Them)

1) “They Never Fight”: Unnatural Passivity Between Two Players

A big red flag is when two specific accounts rarely play big pots against each other, especially when they do play big pots against everyone else.

What this can look like:

Frequent check-backs in spots where value is standard.
Weirdly low c-bet frequency against one opponent but normal versus others.
Overfolding to each other’s bets, even with correct pot odds or strong bluff-catchers.
Repeated “mercy checks” on rivers where the bettor should be thin-value betting.

Why it matters: if two players are avoiding variance against each other, they’re protecting a shared bankroll edge. Even “small” soft play changes your EV massively when it repeats.

Practical check: filter your database for hands involving Player X and Player Y. Compare:

Aggression frequency vs each other vs vs the field
River bet frequency in heads-up pots
Showdown rate and average pot size when they face each other

If “X vs Y” looks like a different sport than “X vs everyone,” pay attention.

2) The “Always There” Teammate: Suspicious Overlap in Session Times & Tables

Colluders often show up together. Not once. Not “occasionally.” Consistently.

Clues:

The same two (or three) screen names appear together across multiple days.
They sit at the same tables even when the lobby has plenty of alternatives.
They join/leaving within minutes of each other repeatedly.
In fast-fold pools, they seem to “collide” unusually often.

Why it matters: random overlap happens. But persistent overlap—especially when it’s paired with soft play—moves from coincidence into signal.

Practical check: keep a simple log:

Date / time / stakes / table name (or pool)
Names you suspect
Notable hands (hand IDs)

Over a couple weeks, you’ll either see the pattern fade (variance / coincidence) or tighten.

3) “Squeeze Insurance”: Coordinated Preflop Lines That Trap a Target

Team play preflop often has a “shape,” especially when they’re targeting one weaker player.

Common shapes:

Teammate A opens, target calls, teammate B 3-bets large from position, and teammate A cold folds too often (or only continues with premiums), keeping the pressure on the target.
Teammates flat more than normal in multiway spots, then take turns applying pressure to isolate the same player.
One account plays “gatekeeper,” entering pots that keep the fish in, while the other account attacks postflop.

Why it matters: these lines can be profitable without obvious dumping. They’re using coordinated ranges to farm someone who can’t defend multiway and multi-street pressure.

Practical check: review hands where:

Both suspects are involved and there is a third player (especially a known recreational).
Look for repeated scripts: open → call → 3-bet → unusual folds / unusual calls.

4) “Perfect Folds” and “Perfect Calls” in the Same Spots

No one plays perfectly. Not you, not me, not the best regs. A consistent string of hero folds/calls specifically when a partner is involved can be telling.

Examples:

Suspect folds a strong bluff-catcher in a spot where population massively overbluffs—but only versus one particular opponent.
Suspect makes “soul reads” at a frequency that doesn’t match their overall style.
They avoid thin value spots against each other yet snap thin value against others.

Why it matters: if they’re sharing info (even something as small as “I folded top pair”), their decisions get unnaturally clean.

Practical check: mark “weird decisions” with notes and re-check later. If the weirdness is opponent-specific, that’s a red flag.

5) Multiway Checkdowns That Don’t Make Sense

Collusion often surfaces in multiway pots where two suspects both reach later streets with a third player involved.

Signals:

They repeatedly check turns/rivers in spots where one of them should be value betting (especially when the third player is weak and likely to call).
The action feels like it’s “designed” to get to showdown cheaply.
One suspect makes small bets that price in the other suspect but price out the third player.

Why it matters: two players coordinating can create a “protected lane” where they reduce risk against each other while extracting from the third player.

Practical check: filter multiway pots that include both suspects and look at:

Turn & river aggression
Bet sizing relative to pot and relative to the third player’s stack
Who benefits most from the chosen line

6) Tournament-Specific Collusion: Bubble & ICM Weirdness

In MTTs, collusion can be especially damaging near pay jumps, bubbles, and final tables.

Watch for:

Two stacks “refusing” to clash even when one has a huge chip EV shove/call.
Repeated min-raises and folds that look like chip “positioning” for a teammate.
Odd all-ins where one suspect jams into another in a spot where calling is a disaster—but the call happens anyway (or vice versa).
“Accidental” chip transfer lines disguised as punts.

Practical check: look at hands late in tournaments:

Are these two players colliding less than you’d expect given stack sizes and positions?
Do their ranges suddenly tighten against each other while staying normal versus others?
Do they take lines that are bad for themselves but great for the other?

HUD & Database Red Flags (Useful, But Don’t Worship Them)

Stats can help, but they’re not proof on their own. What you’re looking for is opponent-specific distortion.

Good comparisons:

3-bet% vs Player Y compared to overall 3-bet%
Fold to 3-bet vs Player Y compared to baseline
River bet% heads-up vs Player Y vs vs field
WTSD% (Went to Showdown) and W$SD (Won at Showdown) in pots vs Player Y
Hands played together count vs expected overlap (rough sanity check)

A single stat spike can be noise. Multiple stats pointing the same direction—over a real sample—becomes a story.

What People Mistake for Collusion (So You Don’t Go Crazy)

Before you label something “team play,” rule out the most common false positives:

Reg avoidance: two strong players naturally avoid marginal spots against each other.
Population underbluffing: “good folds” might simply be correct at your stake.
Table dynamics: if a whale is seated, everyone’s ranges change around that player.
Short sample illusions: 200 hands can create any narrative you want.
Style mismatch: a nit folding to aggression isn’t collusion; it’s Tuesday.

The key difference: collusion creates repeatable, opponent-specific patterns that persist across sessions and tables.

A Simple “Collusion Suspicion Checklist”

Use this as your quick mental model:

If you suspect two accounts, ask:

Do they appear together often (across days, not just one session)?
Do they play unusually soft/passive specifically against each other?
Do multiway pots involving both suspects show strange checkdowns or sizing?
Do preflop lines look coordinated to isolate or pressure the same target?
Do their decisions get “too clean” (perfect folds/calls) in each other’s pots?

If you’re hitting 3+ consistently, it’s worth documenting properly.

What To Do If You Suspect Collusion (The +EV Response)

1) Don’t confront them at the table

Accusing in chat is usually useless and sometimes harmful:

It gives them feedback to adjust.
It can tilt you.
It can create noise if you later report.

2) Start collecting clean evidence

Save:

Hand IDs / HH files
Dates and times
Notes on repeated patterns (“soft play vs each other,” “multiway checkdowns,” etc.)
Any table list screenshots if available

3) Adjust strategically (without leveling yourself)

Until you know more:

Avoid marginal multiway spots involving both suspects.
Reduce bluff frequency in lines that feel “information-sensitive.”
Table change if the game quality drops.

4) Do not let your guard down, just because you play in popular poker site

t’s also worth keeping your expectations realistic: don’t assume collusion is “impossible” just because a site is official, regulated, or licensed. Good operators invest heavily in security, monitoring, and fair-play tools—but no large ecosystem is immune to bad actors. In fact, the bigger the player pool, the easier it is for coordinated teams to blend in, rotate accounts, and avoid detection for longer stretches simply because there’s so much noise in the data.

Interestingly, smaller private games can be easier to keep safe—not because they’re magically honest, but because the player pool is tighter. When the same names appear regularly, weird patterns stand out faster, communities self-police more effectively, and operators can review behavior with more context. Fewer players means fewer hiding places.

And if you want to take a peek at secure private games where the environment is more controlled and the player pool is smaller and easier to be monitored, you can check out these private poker lobbies.

Final Thought: Your Edge Is Pattern Recognition—Use It Calmly

The biggest danger with collusion isn’t only the money you lose in a single hand. It’s the slow drain of confidence: second-guessing every spot, seeing ghosts, playing scared.

The antidote is simple:

Track patterns
Compare behavior vs baselines
Document and report
Move on to better games

You don’t need paranoia. You need process.