Expectancy Calculator
Expectancy is the average result of one trade, measured in R. It multiplies your win rate by your average win, subtracts the loss rate multiplied by your average loss, then subtracts costs. A positive figure means the strategy makes money over enough trades.
Expectancy per trade
Enter your own numbers from at least 30 recorded trades. Results are in R — multiples of what you risk per trade.
R means one unit of risk. If you risk $200 a trade, 1R is $200 and an expectancy of 0.18R is $36 per trade on average.
Runs entirely in your browser. Nothing you type is sent anywhere or stored.
Covered on this page: TradingView.
What it computes
Expectancy is the average result of one trade, expressed in R — multiples of what you risk. It is the one figure that answers whether a strategy makes money, and it needs three inputs that most traders already have and rarely combine.
The formula is a weighted average. Multiply the win rate by the average win, subtract the loss rate multiplied by the average loss, then subtract the cost of transacting:
Expectancy = (win rate × average win) − (loss rate × average loss) − cost
Every term is in R, which is what makes it comparable. A trader risking $50 and one risking $5,000 can put their records side by side, because both are measured against their own risk rather than in currency.
Positive means the strategy makes money over enough trades. Negative means it does not. There is no third answer, and no amount of discipline converts a negative expectancy into a positive one.
Why win rate alone tells you nothing
Two strategies with opposite win rates can have identical expectancy. A method winning 40% of the time at 2R returns 0.8R before costs. A method winning 70% of the time at 0.4R, losing 1R when wrong, returns 0.28R — less than half as much, despite being right nearly twice as often.
Which is why “what is your win rate” is close to a meaningless question. It is one of three inputs, and the least informative of the three, because it is the only one bounded between 0 and 100. The average win has no ceiling.
And it explains a common trap. Cutting winners early raises the win rate and lowers the average win, so it improves the statistic people quote while reducing the number that actually pays.
A worked example
Take the default figures above: a win rate of 40%, winners averaging 2R, losers averaging 1R, and costs of 0.02R per round trip.
The winning side contributes 0.40 × 2 = 0.80R. Four trades in ten win, each returning twice what was risked.
The losing side takes 0.60 × 1 = 0.60R. Six trades in ten lose roughly the full risk.
Costs take another 0.02R, paid on all ten trades regardless of outcome.
So expectancy is 0.80 − 0.60 − 0.02 = 0.18R per trade. Risking $200 a trade, that is an average of $36 per trade and $3,600 over 100 trades — before the variance that makes any short stretch look nothing like it.
The break-even win rate falls out of the same numbers. With a 2R average win and a 1R average loss, you need (1 + 0.02) ÷ (2 + 1) = 34.0% to break even. The strategy wins 40%, so it has six percentage points of margin — and if the win rate drifts to 33%, it stops working.
What the costs actually do
Costs are subtracted from the edge, not from the winners. That is the part people get wrong. Every round trip pays the spread and any commission, and on a quiet day, when price barely moves, that fixed cost is a far larger share of whatever the trade could make.
At the default figures costs take 10% of the gross edge. Small. Now hold the win rate and average loss constant and drop the average win to 0.3R: the gross edge falls to −0.48R and no cost figure rescues it. Conversely at a 0.1R edge, a 0.05R cost removes half of it.
The rule that follows is about frequency, not about entries. Doubling your trade count doubles the cost while leaving expectancy per trade unchanged, so a marginal strategy traded often is a losing strategy and the same strategy traded selectively may not be.
The original data
Of the 24,971 unique videos collected for this site’s search study, win rate appears in 169 at a median of 15,735 views across 136 channels, and position sizing in 195 at a median of 1,738.
The question: Six losses against a positive edge. Stop?
169 videos on one of expectancy’s three inputs. Win rate is intuitive, quotable and bounded; expectancy requires three figures and a record to get them from, and it is the number that decides whether a strategy works.
The variance is why a positive expectancy still feels like failure regularly. At a win rate of 40%, a run of six losses has a probability of about 4.7% on any given six trades — which means it happens roughly every 21 sequences and is entirely ordinary. The expectancy did not change during that run.
When it fails
The largest failure is computing it from too few trades. Thirty trades gives you three numbers with enormous error bars, and the average win is the least stable of them because a single outsized winner moves it a long way. An expectancy calculated from a good month is a description of that month. In the S&P 500 since 1950, the index closed higher ten trading days later 59% of the time — a steady bias that still produces long streaks in both directions, so a short record showing a strong edge is exactly what randomness produces.
The second failure is leaving costs out. The gross figure is not the one you receive, and at high frequency it is not close.
A third is a shifting average loss. Expectancy assumes losers cluster near 1R. If yours run to 1.8R because stops get widened, the arithmetic above is describing a strategy you are not trading.
A fourth is a survivorship-filtered record. Trades you did not log, or a demo period you have excluded, remove the worst results and inflate every input.
A fifth is treating it as a forecast. It is a description of the trades you have already taken, and it holds only while conditions and execution stay similar.
And a sixth is optimizing the win rate because it moved most easily. Cutting winners raises it and lowers expectancy, which is the specific mistake this whole page exists to make visible.
Related
Win rate is the input everybody quotes and the one that matters least on its own. Risk per trade is what defines 1R, and therefore the units every figure here is measured in. And risk management is where expectancy sits inside the wider set of decisions that keep an account alive.
This is the number worth seeing first. It is tempting to spend a long time trying to raise the win rate, which is the most intuitive thing to optimize and very nearly the least useful. Raising the average win does more, and it is the half nobody talks about because a high win rate feels like being right and a high average win feels like getting lucky.
— Michael Whitman
This page is educational, not financial advice. Test every idea on your own charts before risking money. Some links on this page earn a commission if you buy through them. It costs you nothing and it does not decide what appears here or in what order — how these pages are made is set out in our methodology.