This free expectancy calculator tells you what your trading method earns or loses per trade, on average. Enter your winning-trade percentage, your average winning trade, and your average losing trade. The tool returns your expectancy in dollars and in R multiples, plus a projection per 100 trades. Add your trades per month and it projects a monthly figure too. It runs entirely in your browser. Nothing gets uploaded, and no signup is needed.
Trading Expectancy Calculator
If 45 of your last 100 closed trades won, enter 45.
Total profit from winners divided by the number of winners.
Total loss from losers divided by the number of losers. Enter 100, not -100.
Leave blank to skip the monthly projection.
How to use the expectancy calculator
The workflow takes one minute. Pull the numbers from your trading records, not from memory. Memory flatters everyone. Your journal does not.
- Enter your winning-trade percentage. Count your closed trades, count the winners, and divide. If 45 of 100 trades won, enter 45.
- Enter your average winning trade in money. Add up the profit from all winners, then divide by the number of winners.
- Enter your average losing trade as a positive number. Add up the losses, divide by the number of losers, and drop the minus sign.
- Optionally, enter how many trades you take per month. The tool then adds a monthly projection.
- Press Calculate. Read the dollar figure, the R figure, and the verdict line.
Use closed trades only, and include spread, commission, and swap in each result. Costs matter. A method that looks positive before costs can turn negative after them. Also, breakeven trades count in the total but sit in neither average. If you have fewer than 100 closed trades, treat every output as a rough sketch. The sample-size section below explains why.
Worked example: 45% winners, $150 average win
Say your journal shows 45% winners. Your average winning trade is $150. Your average losing trade is $100. Plug those into the tool.
Here is the arithmetic. Wins contribute 0.45 × $150 = $67.50 per trade. Losses subtract 0.55 × $100 = $55.00 per trade. The difference is $67.50 − $55.00 = $12.50 per trade. That is your expectancy.
Now convert to R. Divide by the average loss: $12.50 ÷ $100 = 0.125R. Each trade risks one unit and returns an eighth of a unit on average. Over 100 trades, the projection is $1,250. At 20 trades per month, that is roughly $250 per month — on paper, before variance and before any change in market conditions.
Notice what this example proves. A method that loses more often than it wins can still carry a positive edge. The average win is 1.5 times the average loss, and that ratio does the heavy lifting. See where your own ratio sits with the risk-reward calculator.
Download the complete indicator database
Put your expectancy numbers to work with tested tools on your chart. One email unlocks the full library of 1,380+ indicators with compiled MT4 and MT5 files, plus my TradingView scripts. No paywall, no spam, unsubscribe any time.
Get the complete indicator library
One email unlocks 1,380+ indicators with compiled MT4 and MT5 files, plus my TradingView scripts.
The expectancy formula explained
The formula is a single line of arithmetic:
Expectancy = (Winning % × Average Win) − (Losing % × Average Loss)
The first term is what winners contribute per trade, spread across all trades. Losers take away the second term. The gap between them is your edge, or the lack of one. Divide the result by the average loss and you get expectancy in R. That version travels well because it ignores account size and lot size.
The R form also exposes the breakeven line. Write R as average win divided by average loss. Then expectancy hits zero exactly when your winning percentage equals 1 ÷ (1 + R). With a 2:1 reward ratio, you break even at 33.3% winners. With 1:1, you need 50%. The breakeven calculator maps this curve for any ratio you enter.
Expectancy answers one question: is the edge positive? It does not tell you how much to stake on it. That second question belongs to position sizing, and the Kelly criterion calculator uses exactly the same three inputs to attack it. Run expectancy first. Sizing a negative edge just picks the speed of the decline.
Thirty trades tell you almost nothing
Here is the uncomfortable part. Your inputs are estimates, and estimates carry error bars. A true 45% method can easily print 12 winners in 30 trades, which looks like 40%. It can also print 17, which looks like 57%. Same method, wildly different calculator outputs. Thirty trades cannot separate a real edge from noise.
The error shrinks slowly. Roughly speaking, quadrupling the sample only halves the uncertainty. One hundred trades give you a usable first read. Several hundred start to mean something. This is why a hot month proves little and a cold month disproves little.
Average win and average loss are even more fragile than the percentage. One outlier trade can drag the average and flip the sign of the whole result. Recalculate with your best trade removed. If the edge disappears, the edge was one trade.
The fix is boring and effective: log every trade. A written record with entry, exit, size, and costs turns guesses into data. The trade journal is built for exactly this, and it feeds clean numbers straight into this calculator. Update your inputs monthly and watch how stable they are. Stability is evidence. Drift is a warning.
Positive expectancy still produces losing streaks
A positive number in the result box does not smooth the ride. Expectancy is an average, and averages hide streaks. A 45% method has a 30% chance of losing any two trades in a row. Streaks of five, six, or seven losers are routine over a few hundred trades. The math expects them, even when the trader does not.
Two tools quantify the pain. The risk-of-ruin calculator takes your winning percentage and risk per trade, then estimates the odds of hitting a drawdown you cannot recover from. The drawdown calculator shows the gain needed to climb out of a given hole. A 20% drawdown needs 25% to recover. A 50% drawdown needs 100%.
The practical defense is small, consistent risk per trade. Size positions so a normal streak stays survivable, using the position size calculator. Expectancy tells you the edge exists. Risk control keeps you solvent long enough to collect it.
There is a psychological angle too. Traders abandon sound methods mid-streak, right before the average reasserts itself. Knowing your streak math in advance makes a six-trade skid feel expected rather than broken. Write the expected worst streak into your plan and check reality against it, not against your mood.
Expectancy across sample input combinations
The table below runs the formula across common profiles. Every row uses a $100 average loss, so the dollar column doubles as an R comparison.
| Winning % | Average win | Average loss | Expectancy per trade | In R |
|---|---|---|---|---|
| 30% | $300 | $100 | $20.00 | 0.200R |
| 40% | $200 | $100 | $20.00 | 0.200R |
| 45% | $150 | $100 | $12.50 | 0.125R |
| 50% | $100 | $100 | $0.00 | 0.000R |
| 50% | $150 | $100 | $25.00 | 0.250R |
| 60% | $80 | $100 | $8.00 | 0.080R |
| 70% | $50 | $100 | $5.00 | 0.050R |
| 80% | $30 | $100 | $4.00 | 0.040R |
Read the extremes. A trend follower winning 30% of the time matches a 40% swing method, because its winners run three times the loss. Meanwhile, an 80% scalping profile earns less per trade than either, since its wins are tiny. High winning percentages feel good and pay little when the reward ratio is thin. The formula is indifferent to feelings. It only weighs the two sides of the ledger.
Also note the 50% row with equal wins and losses. It sits at exactly zero before costs, which means it sits below zero after them. Any method near that line needs either a better reward ratio or cheaper execution to survive. Run your own broker's spread through the numbers and see which side of zero you actually trade on.
Honest limitations of this tool
Expectancy math has blind spots, and you should know them before trusting any output.
First, it assumes the future resembles the sample. Markets shift. A method tuned to a trending year can stall in a ranging one. Your true winning percentage is not a fixed property, and neither average is.
Second, it compresses a whole distribution into two averages. Two methods can share identical expectancy while one carries rare, violent losses and the other does not. Averages hide tails.
Third, per-trade expectancy says nothing about frequency. A $5 edge taken forty times a month beats a $30 edge taken twice, yet the second looks better in the result box. Compare monthly projections, not single-trade figures.
Fourth, execution erodes paper numbers. Slippage, widened spreads, and missed fills all shave the average win and fatten the average loss. Backtest figures nearly always overstate live results. That gap is why every tool on this site goes through the process described in the Editorial and Testing Policy before release. Apply the same skepticism to your own spreadsheet. Measure live, keep costs in, and let the sample grow before drawing conclusions.
Want the full toolkit? Get the complete database.
FAQ
What counts as a good expectancy per trade?
There is no universal threshold. Anything reliably above zero after costs is workable, and 0.1R to 0.3R per trade is a common range for retail methods. Frequency matters as much as size: a small edge taken often can outpace a large edge taken rarely.
Can a method with 40% winners have positive expectancy?
Yes. Expectancy weighs how much you win against how often you win. At 40% winners, an average win twice the average loss yields 0.2R per trade. Most trend-following methods live in exactly this territory.
Should I include spread and commission in my inputs?
Always. Use the net result of each trade after spread, commission, and swap. Costs hit every trade, so they compress the average win and inflate the average loss. A thin edge measured before costs often does not exist after them.
My expectancy is negative. Should I just risk less per trade?
No. Smaller size only slows the decline; the average outcome per trade stays negative. Fix the method first: cut costs, tighten entries, or let winners run further. Then re-measure on fresh trades before risking more.
Does positive expectancy mean I will profit going forward?
No. The output is an estimate built from a limited sample, and markets change. Losing streaks occur even with a genuine edge, and small samples mislead in both directions. Results are not guaranteed; past performance is not indicative of future results.
Related tools: atr position size calculator, portfolio heat calculator and hedging calculator, plus the full free forex tools directory.
External references
Expected value on Wikipedia · Expected return at Investopedia