You win six trades out of ten and finish down for the week. Nothing is wrong with the calculator. Your average winner simply did not pay enough to cover your average loser.
Win rate describes how often a trade ends positive. It says nothing about how much each outcome contributes to the account.
Count the size of the outcomes
Imagine ten hypothetical trades, each starting with the same $10 planned risk. Call that initial amount 1R. Six trades make $5 each, or +0.5R. Four lose $10 each, or −1R.
| Outcome | Number | Result each | Total |
|---|---|---|---|
| Winner | 6 | +0.5R | +3R |
| Loser | 4 | −1R | −4R |
| All trades | 10 | 60% win rate | −1R |
The account is down $10 before costs. Average expectancy in this sample is (0.60 × 0.5R) − (0.40 × 1R) = −0.10R per trade.
Find the break-even point
With average wins of 0.5R and average losses of 1R, the pre-cost break-even win rate is 1 ÷ (1 + 0.5), or about 66.7%. Add costs and the required rate rises.
This is arithmetic, not a forecast. It does not mean a strategy will achieve the win rate it needs. It tells you what would have to be true if those average outcome sizes persisted.
Use realised numbers, not the target on the ticket
A planned 2R target does not make the average winner 2R. Partial exits, early closes and scratch trades change the result. Use the net realised profit or loss, including costs, divided by the initial planned cash risk.
Keep the denominator fixed after entry. If you move a stop farther away, do not redefine 1R to make the enlarged loss look ordinary. Record the change separately. Otherwise the metric conceals the behaviour you need to review.
When risk varies between trades, also review the cash result. A large losing trade can outweigh several small wins even if the average R figure looks respectable.
Do not redesign a strategy from ten observations
The example explains why a high win rate can coexist with a loss. Ten trades do not establish the long-term expectancy of an approach. Outcomes cluster, market conditions change and a few unusually large trades can dominate a short sample.
Separate trades that followed the rules from trades that did not. Keep collecting comparable observations. Look at average winner, average loser, net costs, largest loss and the distribution of results alongside the win rate.
One practical journal change is enough for today: add a net R column beside the cash result. At the next review, total both before deciding whether the week felt good. The numbers will not tell the whole story, but they will stop the win count from telling the wrong one.
References & further reading
Forex and CFD trading carries a risk of substantial loss. Examples are hypothetical; analysis is not a personal trading recommendation. Editorial standards · Report a correction.