The metric every trader is missing
Every trader tracks their win rate. Almost none track their skip rate. The gap between the two is where most retail trading losses actually live — not in bad signals, but in good signals that were ignored.
You can have a 65% win rate on your taken trades and still be destroying your returns. If the signals you skipped had a 78% win rate, your judgment is working against you. Standard trading journals don't show you this. Neither do the performance pages on most signal platforms.
Decision Edge Score = Your taken win rate minus your skipped win rate. Positive = you're following the right signals. Negative = you're leaving money on the table.
A concrete example
Let's walk through a real scenario. A trader receives 10 signals in a week. They take 6 and skip 4. Of the 6 taken signals: 4 are wins, 2 are losses — a 67% win rate. Looks solid.
Now check the 4 skipped signals. Three of those 4 hit their take-profit targets. The skipped win rate was 75%. So the trader's taken win rate was 67%, their skipped win rate was 75%, and their Decision Edge Score is 67 − 75 = −8%.
The signal quality is fine. The decision quality is the problem. The trader is systematically filtering out winners.
Why win rate alone is misleading
A 60% win rate sounds good — until you realise you skipped 70% of the winning setups that week. Most signal platforms only show performance for taken signals. Skipped signals disappear entirely from the data.
This creates a blind spot that compounds over time. Traders who consistently skip winners develop an unconscious belief that the AI is underperforming. In reality, their filtering is removing the edge — and they have no number to prove it.
How Traiq calculates your score
Every signal — taken or skipped — is monitored to resolution. The Waiting Entry phase confirms whether actual entry was reached. Shadow monitoring tracks all skipped signals in real time, recording their eventual outcome at TP or SL.
The edge score is computed every Sunday at midnight UTC and updated in your performance dashboard. Positive score displays green. Negative score displays red with the exact size of the gap in percentage points.
What a good edge score looks like
A score of +5% or higher means your signal selection is systematically improving outcomes — you are genuinely filtering noise and following quality setups. A score near 0% means your picks are random — following or skipping makes no measurable difference to outcomes.
A negative score means you have a consistent bias against your best setups. All three readings are useful information. None of them are visible in a standard trading journal.
Can you improve it?
Yes — and knowing the number is the first step. Traders who discover a negative edge score typically identify one of three patterns: they skip signals during high volatility (fear), they skip signals that go against their most recent losing trades (recency bias), or they over-filter setups that the AI has already validated across three timeframes.
The Decision Edge Score does not tell you whether to trade. It tells you whether your judgment is adding or removing value from the AI's analysis. That distinction is worth more than any individual signal.