Expectancy is the average amount a system makes or loses per trade: the win rate times the average win, minus the loss rate times the average loss. A positive expectancy means the strategy makes money over enough trades. It is the one number that decides whether a system works, and win rate cannot replace it.
Most traders never calculate it, which is strange, because it takes four numbers they already have and answers the only question that matters. It also stops the two arguments that consume the most time in trading forums — whether a high win rate is good and whether a big reward-to-risk is better — by folding both into a single figure.
The formula
Expectancy = (win rate × average win) − (loss rate × average loss).
Four inputs, all taken from closed trades in your own record: how often you win, how much you make when you do, how often you lose, and how much you lose when you do. The result is what one more trade is worth to you on average, in advance of knowing anything about it. If the number is negative, no amount of discipline, journalling or screen time changes the destination — only the strategy can.
A worked example: two systems that look nothing alike
Here are two records, both real shapes you will meet. One wins nearly two trades out of three. The other loses nearly two out of three.
| System A | System B | |
|---|---|---|
| Win rate | 65% | 35% |
| Average win | $120 | $400 |
| Average loss | $200 | $150 |
| Expected gain per trade | $78 | $140 |
| Expected loss per trade | $70 | $97.50 |
| Expectancy | +$8 | +$42.50 |
System A wins almost twice as often and is worth roughly a fifth as much per trade. Over 200 trades that is $1,600 against $8,500 — from the strategy that feels far worse to trade. This is the entire case for why win rate is the most overrated number in trading, expressed as arithmetic rather than opinion.
Notice also how thin System A's margin is. An extra $10 of average loss, or two percentage points off the win rate, turns it negative. A system whose expectancy sits within rounding distance of zero is not a system; it is a hobby with commissions.
Express it in R, not dollars
Dollar expectancy breaks the moment you change position size, so professionals state it in R — multiples of the amount risked on each trade. One R is your standard risk. A winner that returns twice what you risked is +2R; a trade stopped out at your invalidation is −1R.
In R, System B above becomes: 0.35 × 2.67R − 0.65 × 1R = +0.28R. Every trade is worth a little over a quarter of what you risk. Risk 1% of the account per trade and that is about 0.28% per trade in expectation, before compounding and before the variance that makes any individual month look nothing like the average.
- R expectancy is comparable across accounts. A $2,000 account and a $200,000 account running the same strategy have the same R expectancy and wildly different dollar figures.
- It survives your growth. Scaling up size changes the dollars and leaves the R untouched, so you can tell whether performance actually changed.
- It plugs straight into planning. Expectancy in R multiplied by trades per month gives you an expected R per month, which is the only honest way to set an expectation.
How many trades before the number means anything
Expectancy is an estimate drawn from a sample, and small samples lie confidently. Thirty trades tells you almost nothing. A hundred starts to be indicative. Several hundred, spread across different market conditions, is where the figure earns trust.
Two checks are worth more than a bigger number. First, split your record into blocks of fifty and calculate each block separately — if expectancy swings from +0.4R to −0.3R between blocks, you have variance rather than an edge. Second, delete your single best trade and recalculate. If the system only works because of one outlier, the honest reading is that you do not yet know whether it works. Keeping the record that makes both checks possible is what a trading journal is actually for.
Why a positive expectancy still is not enough
Expectancy is an average, and averages say nothing about the order results arrive in. A system worth +0.3R per trade will still hand you eight losers in a row at some point, and if each of those is 8% of the account, the average never gets the chance to pay. The maths behind that is set out in risk of ruin, and the practical answer is sizing from risk rather than conviction.
There is also a growth-rate wrinkle. Because losses compound against you, the size that maximises long-run growth is a fraction of what the raw expectancy might tempt you into — the point J. L. Kelly made in his 1956 Bell System Technical Journal paper on optimal bet sizing (Kelly, "A New Interpretation of Information Rate"). Most traders who use it at all trade a half or a quarter of the Kelly fraction, because the full figure produces drawdowns that no human sits through calmly.
And the base rate is unkind. In a study of every individual who began day trading Brazilian equity futures between 2013 and 2015, Chague and Giovannetti found that of those who persisted for more than 300 days, 97% lost money and only 0.4% earned more than a bank teller, defined as US$54 per day (Chague & Giovannetti, "Day Trading for a Living?", University of São Paulo working paper, 2019). Persistence alone does not create expectancy. Measuring honestly, and stopping when the number says stop, is the part almost nobody does.
Frequently Asked Questions
How do you calculate trading expectancy?
Multiply your win rate by your average winning trade, then subtract your loss rate multiplied by your average losing trade. If you win 40% of trades with an average win of 300 dollars and lose 60% with an average loss of 150 dollars, expectancy is 120 minus 90, or 30 dollars per trade. Use closed trades only, and take costs out first.
What is a good expectancy in trading?
Expressed in R, where one R is the amount risked per trade, an expectancy above 0.2R is a genuinely useful system and anything above 0.5R is unusual and deserves suspicion until the sample is large. What matters more than the level is that the figure is positive after all costs and stable across different market conditions rather than produced by a handful of outliers.
How many trades do you need to trust your expectancy?
Treat anything under 30 trades as noise and 100 as the point where a figure starts to be indicative rather than decorative. Systems with low win rates and large winners need more, because the result depends on catching rare big moves. Splitting your record into blocks of 50 and comparing them tells you more than one number from the whole sample.
Can a system with positive expectancy still blow up an account?
Yes. Expectancy is an average per trade and says nothing about the order the results arrive in. A positive-expectancy system sized too large can be finished by an ordinary losing streak before the average has time to assert itself. Expectancy tells you whether a system is worth trading; position sizing decides whether you are still there when it pays.
Bottom line
Expectancy turns four numbers you already have into the only verdict that counts: what one more trade is worth. Calculate it net of costs, state it in R so it survives changes in size, insist on a sample large enough to mean something, and check that it does not depend on a single trade. Then size so that the average has time to arrive. The wider framework this sits inside is risk management in trading, and the discipline that produces measurable trades in the first place is a written trading plan.