Expectancy Calculator — What Your Trading System Earns Per Trade

Expectancy is the single number that tells you whether a trading system has a positive edge. It answers a deceptively simple question: across a large number of trades, how much do you expect to make or lose on each one? Rather than judging a strategy by a flashy win rate or one outsized winner, expectancy blends how often you win with how much you win and lose, producing a probability-weighted average outcome per trade.

This calculator uses the standard per-trade form E = (Win% × AvgWin) − (Loss% × AvgLoss). Feed it your win rate, your average winning trade, and your average losing trade, and it returns the expected value of taking one more trade under that system. A positive result means the math is on your side and the strategy compounds over time; a negative result means the system bleeds capital no matter how disciplined you are about everything else.

Why expectancy matters

A high win rate feels good but proves nothing on its own. You can win 90% of the time and still go broke if the occasional loss dwarfs your typical gain. Expectancy is the antidote to that illusion: it forces win rate and reward-to-risk to sit in the same equation, so you can see whether the wins genuinely outweigh the losses once both frequency and size are accounted for.

For disciplined risk management, expectancy is the foundation everything else is built on. Position sizing, drawdown tolerance, and growth projections all assume you are deploying capital into a positive-expectancy system. If expectancy is zero or negative, no amount of clever sizing will save the account — better sizing only changes how fast you lose. Confirming a positive edge first is the prerequisite for every other decision.

Expectancy also reframes losing trades correctly. When you know each trade is worth, say, a positive 0.3R on average, a string of losers becomes statistical noise rather than evidence the system is broken. That separation between process and outcome is what lets traders keep executing a proven edge through the inevitable rough patches.

The formula

E = (Win% × AvgWin) − (Loss% × AvgLoss)

EExpectancy — the average profit or loss per trade, expressed in the same units as your average win and average loss (currency, ticks, points, or R).

Win%Win rate — the probability of a winning trade, as a decimal (e.g. 0.45 for 45%). This is winning trades divided by total trades.

AvgWinAverage win — the mean profit of your winning trades, taken as a positive number.

Loss%Loss rate — the probability of a losing trade, as a decimal. With no scratch trades, Loss% = 1 − Win%.

AvgLossAverage loss — the mean loss of your losing trades, entered as a positive magnitude; the formula already subtracts it.

Keep AvgWin and AvgLoss in the same unit, and enter AvgLoss as a positive number — the minus sign in the formula handles the direction. Win% and Loss% should sum to 1. If you book breakeven or scratch trades, treat them as a third bucket with zero average and adjust the probabilities so all three sum to 1.

Worked example: a 40% win rate trend system

· A swing system wins on 40% of trades, so Win% = 0.40 and Loss% = 0.60.
· Across the sample, winning trades average +$900 and losing trades average −$300 (entered as $300).
· You risk a fixed $300 per trade, so the average win is effectively 3R and the average loss is 1R.

Weighted win contribution0.40 × $900 = $360

Weighted loss contribution0.60 × $300 = $180

Expectancy per trade$360 − $180 = $180

Expectancy in R terms$180 ÷ $300 risk = 0.60R per trade

Projected over 200 trades200 × $180 = $36,000

Despite losing 60% of the time, the system earns about $180 (0.60R) per trade on average because winners are three times the size of losers.

How to use it

01Pull at least 30–50 closed trades from your journal so the averages are statistically meaningful.
02Enter your win rate as a percentage — winning trades divided by total trades.
03Enter your average win: the mean profit across only your winning trades.
04Enter your average loss as a positive number: the mean loss across only your losing trades.
05Read the expectancy result — a positive figure is your expected profit per trade; a negative figure means the system loses money on average.
06Optionally divide expectancy by your average risk per trade to express the edge in R, which makes it comparable across markets and account sizes.

Common mistakes

Chasing win rate instead of expectancy

A 70% win rate looks impressive but is worthless if the losses are large. Always weight win rate against reward-to-risk — expectancy is what actually grows the account.

Using too small a sample

Expectancy computed from ten trades is mostly luck. A handful of outlier wins or losses can flip the sign entirely; gather a few dozen trades before trusting the number.

Entering the average loss as a negative

The formula already subtracts the loss term, so AvgLoss must be a positive magnitude. Entering −$300 double-negates it and inflates expectancy.

Ignoring costs and slippage

Commissions, spread, and slippage shrink every average win and enlarge every average loss. Use net figures, not gross, or the edge you measure will not exist in your live account.

FAQ

What is a good expectancy?

Any positive expectancy means the system makes money over time, so above zero is the first hurdle. Expressed in R, many robust systems sit between 0.1R and 0.5R per trade; higher is rarer and worth scrutinising for overfitting or too small a sample.

What is the difference between expectancy and expectancy in R?

Dollar expectancy depends on your position size, while R expectancy divides the result by the amount risked per trade. R-based expectancy is unit-free, so you can compare a forex scalp to an equities swing trade on the same scale.

How many trades do I need before expectancy is reliable?

There is no hard cutoff, but 30 trades is a rough minimum and 100 or more gives far more stable averages. The more your strategy depends on infrequent large winners, the larger the sample you need.

Can a system with a low win rate still be profitable?

Yes. A trend-following system might win only 35–40% of the time yet be highly profitable because the winners are several times larger than the losers. Expectancy captures exactly this trade-off.

How do breakeven or scratch trades affect expectancy?

Treat them as a separate bucket with an average of zero and include their frequency so all probabilities sum to 1. They drag expectancy toward zero by diluting the share of trades that win or lose, without adding profit or loss themselves.

Does positive expectancy guarantee I will make money?

No — it means the odds favour you over a large sample, not on any single trade. You still need enough capital and a sane position size to survive the inevitable losing streaks long enough for the edge to play out.