Win Rate vs Win/Loss Ratio: Same Wins, Two Different Numbers
Win rate divides wins by all trades; win/loss ratio, by losses. How to convert one into the other, and what neither one shows you: trade size.
Win rate divides wins by every trade. Win/loss ratio divides wins by losses. The same 60 trades come out as 58.3% on one measure and 1.4 on the other, and one line of arithmetic turns either number into the other. Neither one tells you how much each win made or each loss cost.
Win rate: wins divided by every trade taken
Win rate answers one question: what share of all trades won? Divide the wins by the total number of trades and multiply by 100 for a percentage. The result always falls between 0% and 100%.
It also works in reverse. To get a count of wins, Omni Calculator multiplies the winning percentage by the number of attempts: 40% of 15 is 6 wins.
Win/loss ratio: wins divided by losses
The ratio leaves the total out. It divides wins by losses, so it has no upper limit. Per Investopedia, a ratio above 1.0 means there were more winning trades than losing trades. At exactly 1.0 the two counts are equal. Below 1.0, losses outnumber wins.
One record, two numbers: 35 wins and 25 losses
Take one worked example, with made-up numbers: a record of 35 wins and 25 losses, 60 trades in total.
- Win/loss ratio: 35 ÷ 25 = 1.4, or 1.4 wins for every loss.
- Win rate: 35 ÷ 60 = 0.583, a win percentage of 58.3%.
Both numbers describe the same 60 outcomes. The difference is the denominator: the ratio compares wins with losses, and the rate compares wins with everything.
Convert with rate ÷ (1 − rate), unless breakeven trades are counted
When every trade is either a win or a loss, the two numbers hold the same information:
- Rate to ratio: ratio = rate ÷ (1 − rate). The worked example’s 58.3% gives 0.583 ÷ 0.417 ≈ 1.4, the same as 35 ÷ 25.
- Ratio to rate: rate = ratio ÷ (1 + ratio). A ratio of 1.4 gives 1.4 ÷ 2.4 ≈ 0.583, or 58.3%.
- Counts: Omni Calculator’s 40% of 15 is 6 wins, which leaves 9 losses, so the ratio is 6 ÷ 9 ≈ 0.67. That matches 0.4 ÷ 0.6.
The formula stops a common misreading. In Investopedia’s example of 12 wins and 18 losses, the ratio is 12 ÷ 18 ≈ 0.67, and the page says this “means that you are losing 67% of the time.” The conversion says otherwise: 0.67 ÷ 1.67 ≈ 0.40. So 12 of the 30 trades (40%) won and 18 ÷ 30 = 60% lost. A ratio is not a share of trades. Read the right way, the worked example’s 1.4 still leaves 25 of 60 trades lost (25 ÷ 60 ≈ 42%).
Breakeven trades (trades closed at no gain and no loss) break the shortcut. Example, with made-up numbers: add 10 breakeven trades to the 35-and-25 record. The win rate drops to 35 ÷ 70 = 50%, but the ratio stays at 35 ÷ 25 = 1.4. The formula would wrongly give 0.5 ÷ 0.5 = 1.0. Before you convert, check whether a report counts breakevens in its total.
Neither number shows how big each win and loss was
Both measures count trades. Neither one weighs them. Investopedia says the win/loss ratio ignores how much money each trade gained or lost. Win rate has the same blind spot because it is built from the same counts. Example, with made-up numbers: a trade that gains $500 and a trade that gains $5 each add exactly one win.
That is why, per Investopedia, a high win rate combined with a poor risk/reward ratio can still produce losses. A string of small wins can be wiped out by a few large losses, and neither count would show it.
Expectancy adds the trade sizes both counts leave out
Two more inputs fill the gap. Per Hoc-Trade, the risk-reward ratio divides your average winning trade by your average losing trade, so 3:1 means the typical win is three times the typical loss. In the arithmetic below, R stands for one average loss, so results read in units of that loss instead of dollars.
Expectancy, the average result per trade, is worked here from those inputs:
expectancy = (win rate × average win) − (loss rate × average loss)
The standard textbook case compares a 40% win rate at 3:1 reward-to-risk with a 70% win rate at 1:1, as Hoc-Trade sets it out.
Hoc-Trade’s example: 3.5 times the win/loss ratio, 0.2R less per trade
In this example, the record with the lower win/loss ratio has the higher average per trade. All averages below are before costs.
| Record | Win rate | Win/loss ratio = rate ÷ (1 − rate) | Reward-to-risk | Average per trade, before costs |
|---|---|---|---|---|
| Worked example above: 35 wins, 25 losses | 58.3% | 0.583 ÷ 0.417 ≈ 1.4 (35 ÷ 25) | not given | needs win and loss sizes |
| Investopedia: 12 wins, 18 losses | 40% | 0.4 ÷ 0.6 ≈ 0.67 (12 ÷ 18) | not given | needs win and loss sizes |
| Hoc-Trade trader A | 40% | 0.4 ÷ 0.6 ≈ 0.67 | 3:1 | 0.4 × 3 − 0.6 × 1 = 0.6R |
| Hoc-Trade trader B | 70% | 0.7 ÷ 0.3 ≈ 2.33 | 1:1 | 0.7 × 1 − 0.3 × 1 = 0.4R |
Gap: trader B’s win/loss ratio is 2.33 ÷ 0.67 ≈ 3.5 times trader A’s, yet B averages 0.6R − 0.4R = 0.2R less per trade.
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
Read neither count alone; put the trade sizes beside it
The win/loss ratio is easy to mistake for a percentage, as the Investopedia example shows. And the example that shows the size problem most clearly is itself only an illustration: Hoc-Trade calls the 40%-versus-70% figures “made-up examples” that nobody checks against real traders. It shows how the arithmetic works. It does not describe any real trader’s record.
So if you are comparing two trade records or reading a backtest report, do not rely on either count by itself. Use win rate for the share of trades that won. Convert it to a ratio only when breakeven trades are left out of the total. Put average win, average loss and expectancy next to it before you compare anything.
How we evaluated
Each definition and sourced example comes from the pages linked inline. Omni Calculator supplies the reverse win-rate arithmetic, Investopedia the meaning of the ratio and what it leaves out, and Hoc-Trade the textbook comparison. The 35-and-25 record is our own worked example; it, the conversion formulas, the breakeven check and the per-trade averages are arithmetic worked from those figures and shown in full on the page. Hypothetical figures carry the hypothetical-performance statement from CFTC Rule 4.41.
FAQ
Is a win/loss ratio of 1.4 the same as winning 58.3% of trades?
Yes, as long as every trade is either a win or a loss. 1.4 ÷ 2.4 ≈ 0.583, which matches 35 ÷ 60 in the worked example above. Once breakeven trades are in the total, the two numbers no longer convert.
Does a high win rate mean a trading record made money?
No. Per Investopedia, a high win rate with a poor risk/reward ratio can still produce losses.
Which numbers belong in a trading journal?
Both counts, plus average win and average loss. The counts tell you how often trades won. Only the averages tell you how much each win and loss was worth, and expectancy puts the two together.
