Trading Expectancy: The Only Formula That Tells You If You Have an Edge

Most traders can quote their win rate. Very few can tell you what one more trade is worth to them, and that is the number that decides whether the account grows.

Expectancy answers it in one line of arithmetic. It is also the fastest way to prove that a 70 percent win rate can lose money and a 35 percent win rate can pay rent.

Win Rate Alone Tells You Nothing

Take two traders.

The first wins 7 trades out of 10. It feels excellent. She cuts winners early at 80 dollars and lets the losers run to 200 before she folds.

The second wins 4 out of 10, loses more often than he wins, and finds the whole experience uncomfortable. His winners average 300 dollars against 100 dollar losses.

Over 200 trades the first trader is down and the second is up five figures. Nothing in either win rate tells you that. You need both sides of the trade, and that is exactly what expectancy combines.

The Formula

Expectancy = (Win rate x Average win) - (Loss rate x Average loss)

Three rules for using it without fooling yourself:

• Enter the average loss as a positive number. The minus sign in the formula is already doing that work.
• Loss rate is 1 minus the win rate, both as decimals. A 40 percent win rate is 0.40, so the loss rate is 0.60.
• Use net figures. Spread, commission and swap come out before you average anything, or your edge exists only in a world with no costs.

The output is money per trade. Not per winning trade, not per good week. Per trade, including the losing ones, averaged over the sample you fed it.

Three Traders, One Number

Same formula, three real-looking sets of numbers.

Trader A. High win rate, upside down. 70 percent win rate, 80 dollar average win, 200 dollar average loss.

(0.70 x 80) - (0.30 x 200) = 56 - 60 = -4 dollars per trade

She wins more than twice as often as she loses and still bleeds 4 dollars every time she clicks. Over 200 trades that is 800 dollars, and every one of her losing months will feel like bad luck rather than arithmetic.

Trader B. Low win rate, real edge. 40 percent win rate, 300 dollar average win, 100 dollar average loss.

(0.40 x 300) - (0.60 x 100) = 120 - 60 = +60 dollars per trade

He loses six trades out of ten. Over the same 200 trades that is 12,000 dollars. The discomfort is the price of the edge, not evidence against it.

Trader C. The thin one. 55 percent win rate, 120 dollar average win, 140 dollar average loss.

(0.55 x 120) - (0.45 x 140) = 66 - 63 = +3 dollars per trade

Positive, and almost nothing. A wider spread, a broker commission change or two skipped stop losses put Trader C underwater. Thin positive expectancy is the most dangerous state to be in, because it looks like a working system right up until it stops being one.

The Same Formula in R

Dollars break the moment your position size changes. If you risked 50 dollars a trade in March and 200 in June, a dollar-based average win is comparing two different games.

R fixes it. One R is the amount you risk on the trade, so a full stop-out is exactly minus 1R and everything else is measured against it.

Expectancy in R = (Win rate x Average win in R) - (Loss rate x 1R)

Trader B again, whose winners average 3R:

(0.40 x 3) - (0.60 x 1) = 1.2 - 0.6 = +0.6R per trade

That number travels. It is the same on a 2,000 dollar personal account and a 100,000 dollar funded account, which is the only reason a backtest can say anything useful about live trading. It also converts back to money the instant you fix a risk level: at 1 percent risk on a 10,000 dollar account, 0.6R is 60 dollars a trade.

A real edge is usually a fraction of an R rather than a whole one, and a fraction is enough: it compounds across every trade you take. If your spreadsheet says 1.5R per trade, check the sample size before you scale up. That is far more often a small sample with one big winner in it than an unusually good strategy.

The Break-Even Win Rate Table

Set expectancy to zero and solve for the win rate:

Break-even win rate = 1 / (1 + R)

Two things fall out of this table.

A high win rate is not an achievement on its own. At 0.5R average winners, 66 percent is break-even. Trader A's 70 percent looked elite and was barely above water before costs pushed her under.

Raising your R target lowers the bar, but not for free. Targeting 3R instead of 1.5R drops your required win rate from 40 to 25 percent, and your actual win rate will drop too, because price has to travel twice as far. The question is never which is better in the abstract. It is whether your win rate falls further than the break-even line does when you extend the target, and that is a question only your own logged trades can answer.

How Many Trades Before the Number Means Anything

This is where most expectancy calculations quietly fail.

Take a 30-trade sample with one 5R winner in it. That single trade contributes 5 divided by 30, which is 0.17R of expectancy on its own. Since a genuine edge is often 0.2R, that one trade is roughly the whole result.

So run this test on your own data before you trust the number: recompute expectancy with your single best trade deleted. If it collapses toward zero or flips negative, you do not have a measured edge yet. You have one good trade and 29 others.

The win rate is noisy on small samples too, and you can size the noise without any study to cite. The standard deviation of the win count over n trades is the square root of n x p x (1 - p).

• At a true 40 percent win rate over 30 trades: the square root of 30 x 0.4 x 0.6 is about 2.7 wins. Ordinary samples run from about 9 to 15 wins, which reads as a win rate anywhere between 30 and 50 percent.
• Over 100 trades: the square root of 100 x 0.4 x 0.6 is about 4.9 wins. The same ordinary range is now 35 to 45 percent.

Same strategy, same trader, half the uncertainty. Nothing changed except the sample.

This is the honest case for backtesting rather than a reason to avoid it. Take two or three trades a week and a hundred-trade sample is most of a year of waiting. Replaying historical price bar by bar produces those hundred setups in a few afternoons, and if you tag them with the same setup conditions they land in the same statistics as your live trades. Our bar replay backtesting guide covers the method, including how to stop hindsight from inflating the exact number you are trying to measure.

Four Ways Expectancy Lies

1. Mixed position sizing. Averaging dollar wins across periods where you risked different amounts produces a number that describes no strategy you ever traded. Use R.

2. Break-even trades counted carelessly. A scratch at zero is neither a win nor a loss, but it has to go somewhere in the denominator. Dropping break-evens raises your win rate. Counting them as losses lowers it. Neither is wrong, but switching between them mid-analysis is how people accidentally prove whatever they hoped. Pick one convention and keep it.

3. Costs left out. Spread and commission come off every trade, winners included. Work it in R and the scale is obvious: if you risk 100 dollars a trade and pay 4 dollars round-turn in spread and commission, that is 0.04R gone from every trade. Against an edge of 0.2R, costs are a fifth of it. Expectancy calculated on gross P&L is a marketing number.

4. A strategy that changed underneath you. If you moved from London opens to New York opens in April, one expectancy figure across both is an average of two different systems. Filter by strategy and by symbol and compute each separately. That is where the useful answer usually is: the total is fine, one symbol is carrying it, and another has been negative for four months. How to track trading performance walks through the wider set of metrics that expectancy sits inside.

Three Levers That Move It

Only three things go into the formula, so only three things can change the output.

Raise the average win. Usually the largest available gain and the hardest to execute, because it means holding through the give-back. Check whether your winners actually reach a further target before you move it: if your logged trades show price stalling at 1.8R, a 3R target does not raise your average win, it turns winners into break-evens.

Cut the average loss. The fastest and least glamorous fix. It is rarely about stop placement. It is about the trades where you widened the stop, added to a loser, or refused to accept minus 1R. Those trades are visible in a journal precisely because their loss is bigger than your intended risk, which makes them easy to find and count. Revenge trading and how to spot it in your journal covers the pattern that produces most of them.

Raise the win rate by taking fewer trades. Not by being better at reading charts. By dropping the setup that your own data shows is negative. Most journals with more than a hundred trades in them contain at least one condition, session or symbol that quietly funds the losses of everything else.

For prop firm traders there is a fourth constraint the formula does not see: expectancy says nothing about the order the wins and losses arrive in, and an evaluation can be failed by a drawdown sequence inside a perfectly positive edge. The arithmetic for that is in how to pass a prop firm challenge.

Where Expectancy Lives in TradingSFX

The number is computed for you, on every trade you log, using the formula above.

• Dashboard. An Expectancy tile that switches between dollars and R, alongside win rate, profit factor and current streak. Available on the free plan.
• Break-even handling is yours to set. A single toggle decides whether scratch trades are ignored, counted as wins or counted as losses, and the setting applies to every statistic on the page at once, so your expectancy and your win rate can never be computed under two different conventions.
• Per symbol and per strategy. The detailed analysis view recomputes expectancy for whatever slice you filter to, which is how you find the symbol that is carrying the account and the one that is draining it.
• PDF performance report. Expectancy per trade appears in the printable report for a mentor or a prop firm, on Pro and above.

You can look at all of it running on sample data first, no account needed, in the detailed analysis demo.

Bottom Line

Expectancy is one line of arithmetic that ends the argument about whether a strategy works. Win rate cannot do it. Total profit cannot do it, because it hides how much risk bought the profit.

Compute it in R, on net numbers, over a sample big enough that deleting your best trade does not change the answer. If it is positive and it survives that deletion, your job is repetition and position sizing. If it is negative, no amount of screen time fixes it, because you are being paid a negative amount per click and clicking more only settles the account faster.

The only requirement is trades logged with an entry, an exit and a stop, which is the same data the formula has always needed. TradingSFX Basic is free forever at 10 trades a month, which is enough to see the number and start arguing with it.

Published August 3, 2026. All figures in this article are arithmetic worked openly from the stated inputs. No survey data, study results or user statistics are cited, and no competitor pricing is quoted.