Average Win / Average Loss
Also known as: avg win, avg loss, win-loss size ratio, payoff ratio, average win average loss ratio, reward-to-risk realised
What is it?
Average win and average loss are two simple numbers that describe how big your typical winning trade is versus how big your typical losing trade is. The average win is the mean profit across all your winning trades, and the average loss is the mean loss across all your losing trades. Dividing one by the other gives a ratio that tells you, on a per-trade basis, how much you make when you are right compared with how much you give back when you are wrong.
| Across your last 100 trades | Typical winning trade | Typical losing trade |
|---|---|---|
| Average size of the trade | +$200 (average win) | -$100 (average loss) |
| How they compare | Twice the size of a loser | Half the size of a winner |
| Win / loss size ratio | $200 / $100 = 2 to 1 | A typical winner is 2x a loser |
| But read it next to win rate | 70% win rate survives a smaller ratio | 30% win rate needs an even bigger one |
| The trap to avoid | Letting winners run their plan | Cutting winners early, letting losers run |
For example, if your last hundred trades produced winners averaging 200 dollars and losers averaging 100 dollars, your average win to average loss ratio is 2 to 1, meaning a typical winner is twice the size of a typical loser. This number means nothing on its own, though, and that is the trap: it must be read alongside your win rate. A strategy that wins only 30% of the time still needs winners far larger than losers to come out ahead, while a strategy that wins 70% of the time can survive smaller winners.
The classic mistake is celebrating a high win rate while quietly running a tiny average win and a huge average loss, because cutting winners early and letting losers run produces exactly that shape and bleeds the account over many trades despite looking good on a screenshot. Together with win rate, the average win to average loss ratio is what actually feeds expectancy, the bottom-line measure of whether the strategy makes money on average. Past performance does not guarantee future results, no approach is risk-free, and your capital is at risk on every trade.
Why it matters: It tells you how much you make when right versus how much you lose when wrong, which is half of what decides whether a strategy is profitable at all.
Average win / average loss ratio = (total profit on winners / number of winners) / (total loss on losers / number of losers)
Together with win rate it determines expectancy, so it directly drives whether the strategy is profitable across many trades.
Real-world example
Over a hundred trades, winners average 200 dollars and losers average 100 dollars, giving an average win to average loss ratio of 2 to 1 historically.
How SignalBots handles it
SignalBots stats pages report average win and average loss per setup as historical estimates next to win rate and drawdown, each linked to /risk-warning, so the figures stay honest across the Web Dashboard, Telegram, and Mobile Apps.
Pro tip
Always read your average win to average loss ratio next to your win rate; neither number tells you if you are profitable on its own.
Common pitfalls
Cutting winners early and letting losers run, which produces a tiny average win against a large average loss that drains the account over time.
Frequently asked questions
Is a higher average win to average loss ratio always better?
Not on its own, because the ratio only matters alongside your win rate. A high ratio with a very low win rate can still lose money over many trades, so judge the two numbers together through expectancy.
What ratio should I aim for?
There is no single correct figure; a lower win rate needs a larger ratio to break even, while a high win rate can work with a smaller one. The right target depends on how often your strategy actually wins.
How do I calculate my average win and average loss?
Add up the profit from all your winning trades and divide by the number of winners, then do the same for losses. These are historical figures from your past trades, not a forecast of future results.
Why can a high win rate still lose money?
Because a high percentage of small winners can be wiped out by a few oversized losers. If your average loss dwarfs your average win, the math turns negative no matter how often you win.
How does this connect to expectancy?
Expectancy combines win rate with the size of your average win and average loss into a single per-trade figure. The average win to average loss ratio is one of the two ingredients that feed it.
Trading involves substantial risk of loss. Historical and backtested results do not guarantee future performance. Read the full risk warning.