Expectancy
Formula
Expectancy ($) = mean(net P&L) over closed = winRate·avgWin − lossRate·|avgLoss| Expectancy (R) = mean(r_multiple) over trades where R is defined
Worked example
Four closed trades: +$500, +$300, −$200, −$100.
| Sum of net P&L | $500 + $300 − $200 − $100 = $500 |
| Trade count | 4 |
| Expectancy ($) | $500 / 4 |
| Result | +$125.00 |
It tells you the long-run value of taking a trade in your system, which is the foundation of position sizing and growth. A positive but small expectancy still compounds with enough volume.
Dollar expectancy mixes different position sizes; expectancy in R normalises by risk and is usually the cleaner read. It is an average — individual trades vary widely around it.
How TradeJournalOS shows it
Shown in dollars on the dashboard, and in R once your trades carry a planned stop (which defines initial risk and therefore R).
Create a free account to see expectancy on your own trades.
Frequently asked questions
What is the difference between dollar expectancy and R expectancy? +
Dollar expectancy is the average net P&L per trade. R expectancy is the average R-multiple, which normalises every trade by the dollars you risked, so trades of different sizes are comparable.
Can expectancy be positive with a low win rate? +
Yes. If your winners are much larger than your losers, you can have a sub-50% win rate and still be positive — that is exactly what payoff ratio and expectancy capture.