Who this is for — Anyone who wants to know whether their method has real statistical edge instead of judging results by feel alone.
Expectancy measures the average expected result per single trade. It is the metric that unites win frequency and the ratio between wins and losses.
In plain terms — It tells you what an average trade of your method is "worth". If it is positive on a robust sample, you are playing a favourable game.
Bronze prerequisite — Before this lesson: drawdown, risk-per-trade, risk-reward-ratio, r-multiple. See bronze-path.
Formula and correct reading
Classic formula:
Expectancy = (win rate × average win) − (loss rate × average loss)
To interpret it reliably:
- Use data net of operational costs.
- Check sample size (sample-size).
- Segment by setup, not only overall total.
Positive but unstable expectancy can indicate dependence on a few outliers.
Example — Win rate 45%, average win 1.8R, average loss 1R. Expectancy = (0.45 × 1.8) − (0.55 × 1) = +0.26R. On average each trade generates 0.26R before any future degradation.
Usage mistakes
- Calculating it over periods that are too short.
- Ignoring slippage and commissions.
- Not updating the figure after market or regime changes.
- Confusing historical expectancy with future guarantee.
Card
- What it is: average expected return per single trade.
- Why it matters: summarises real method efficiency.
- Practical use: compare setups and monitor edge deterioration.
Silver path — Module: Operational metrics. Part of silver-path.