Find the Poker Leaks
Actually Costing You EV
A leak is a recurring decision pattern with enough evidence to act on — not a red number in a HUD.
Not every deviation is a leak.
REQUEST EARLY ACCESS · ALPHA IN PREPARATION
REQUEST EARLY ACCESS · ALPHA IN PREPARATION
Post-session analysis only. No real-time assistance.
A leak is a repeating decision pattern worth acting on.
A leak is a recurring decision pattern with enough evidence to act on — not a red number in a HUD.
A useful leak has four parts: a repeating decision, enough opportunities to trust the pattern, enough estimated impact to matter, and enough confidence to spend study time on it.
A LEAK IS NOT
- An unusual tracker stat
- One losing hand
- A short downswing
- Any difference from a population average
A USEFUL LEAK IS
- A recurring decision pattern
- Enough evidence
- Enough estimated impact
- Enough confidence to act
A strange number tells you where to look. It does not verify a leak.
Stats are triage signals. Two players can share a frequency and still make very different decisions in the hands underneath it.
SIGNAL
An aggregate frequency looks unusual.
That is a candidate area. It is not a verdict, a solver output, or a confirmed leak.
STILL NEEDS EVIDENCE
- PositionWhere the decision happened.
- Hand classWhich holdings created the frequency.
- Opponent actionWhat the hero was responding to.
- Stack depthWhether the spot was shallow or deep.
- StreetPreflop, flop, turn, or river.
- Pot typeSingle-raised, 3-bet, or other.
- Decision mixWhich actual choices produced the number.
Candidates are places to inspect, not confirmed leaks.
Stats and filters narrow the database to repeating spots. That step produces candidates. Evidence from actual hands is required before a candidate becomes a priority.
- SIGNAL
- FILTER
- REPEATING PATTERN
- EVIDENCE
- SIGNALA frequency or result looks worth inspecting.
- FILTERThe database is sliced by position, street, and pot type.
- REPEATING PATTERNThe same decision family keeps showing up.
- EVIDENCEHands are checked before anything is ranked.
The hands underneath the filter are the evidence.
A candidate becomes useful only when representative decisions repeat. Opportunity count and relevant decisions belong to that family — not to the whole database.
RELEVANT DECISIONS
186
of 412 opportunities
CONFIDENCE
HIGH
for this decision family
BB · Single-raised pot
Called a large river bet after missing
preflop / flop / turn / river
Similar weak bluff-catchers are being continued too frequently in this branch.
CO · 3-bet pot
Called river after a missed draw
preflop / flop / turn / river
Ace-high with no improvement after a passive turn — the same branch, a different runout.
The more frequent pattern is not automatically the larger problem.
Frequency is one input. Estimated impact and confidence also matter. This comparison is an illustrative report output, not a universal ranking formula.
#2
BB vs BTN Defence
−0.31
More relevant decisions
#1
River Bluff Catching
−0.47
Ranked first in the sample
Prioritization can consider recurrence, estimated impact, confidence, and whether the spot is trainable. The product model may evolve. It is not a single frozen equation.
A pattern needs enough opportunities before it deserves a strong claim.
Confidence is about the decision family being inspected. A large database can still leave a narrow turn or river spot under-evidenced.
Total hands are context. Evidence is judged on the relevant opportunities.
412 opportunities
Enough opportunities in this family to support a claim.
37 opportunities
Too few opportunities to verify a leak.
The first study target is the pattern with enough evidence and estimated cost.
Expected impact here is an estimated cost over the sample — not a solver-perfect EV for every node. Ranking also depends on confidence and whether the spot can be trained.
River Bluff Catching
Calling frequency stays high versus large river bets after the hero has missed.
The sample shows a repeating tendency to continue on the river in spots where the opponent's value range is concentrated. The finding is ranked first because the estimated cost and the opportunity count are both material.
Finding a candidate is not the same as verifying a leak.
A leak finder that cannot refuse a claim is just a warning generator. No action and insufficient evidence are first-class results.
River Bluff Catching
Repeating pattern, enough evidence, material estimated impact.
WORK ON THIS
UTG open frequency
Detected, then left off this cycle because the expected impact is small.
NO ACTION
Turn probes in position
The opportunity count is too small to support a leak claim.
INSUFFICIENT
EVIDENCE
The product should produce a short study list, not a wall of warnings.
After a leak is verified and prioritized, the next step is targeted practice on that decision family — then more hands, then the same filter again.
Training on this site is the intended next step after a verified priority. This page is not a live training engine and does not advise current hands.
- FIND
- VERIFY
- PRIORITIZE
- TRAIN
- PLAY
- RE-MEASURE
Prove whether the targeted decisions changed.
The measured object is the targeted decision-pattern frequency — not a short-term winrate swing, and not a claim that training caused the result.
targeted overcall frequency
targeted overcall frequency
Not enough new evidence to mark the leak resolved.
- Evidence before claims.
- Post-session analysis only.
- No real-time assistance.
- AI explains structured evidence. It does not invent hands, samples, or solver outputs.
Common questions
Is a strange stat automatically a leak?
No. Stats are signals. A leak requires a repeating decision pattern, enough opportunities, and a reason to believe fixing it would matter.
Why rank by expected impact instead of frequency?
A common small mistake and a rare expensive river error are not the same problem. Frequency is not cost.
Find your highest-priority leak.
Then train the few decisions that matter.
Find the few decisions worth fixing next.
Post-session analysis only. No real-time assistance.