Narrow CPR Scanner Free Tool — Daily & Weekly NSE Bhavcopy Scanner
Narrow CPR · Stock Scanner
Read article →
There are no items in your cart
Add More
Add More
| Item Details | Price | ||
|---|---|---|---|
Quick Answer: A trading expectancy calculator multiplies your win rate by your average gain, then subtracts your loss rate multiplied by your average loss. The answer is what one trade of that setup is worth on average. Above zero after costs suggests an edge on your sample; zero or below suggests none.
Definition: Expectancy is the average result per trade over many trades, stated in Rs or in R (multiples of your planned risk).
Enter your win rate, average gain and average loss. Get expectancy per trade, break-even win rate, profit factor and more.
Winning trades ÷ total trades × 100
Total profit of winners ÷ number of winners
Enter as a positive number
Brokerage, STT, charges and slippage, simplified
Used only for a monthly projection
On these numbers, an average trade adds about Rs 540 after costs. You need only 28.6% wins to break even, and you are at 45.0%. This is an edge on your sample, not a guarantee. Check that the sample is large enough and costs are realistic.
Formula: Expectancy = (Win Rate × Avg Gain) − (Loss Rate × Avg Loss). Illustrative tool for education, not investment advice. Results depend on the quality and size of your trade sample.
Most traders track one number: win rate. A better question is what one trade of this setup is worth on average. A trading expectancy calculator answers it using three figures already in your journal: win rate, average gain and average loss. Use the free calculator above, then follow the formula, the full worked example in Rs, the break-even win rate for each Reward to Risk Ratio, and the mistakes that make good-looking numbers misleading. Every figure is illustrative, and no outcome is assured.
Trading expectancy is the average amount you can expect one trade of a given setup to add or remove, based on your past results. It blends how often you win with how much you win and lose. A positive number after costs means the setup has an edge on that sample; it does not predict any single trade.
Think of a shop owner who does not care about one sale, only the average margin across thousands. Your trading is the same. A setup that wins 60% of the time can still lose money if the losers are much larger than the winners. A setup that wins only 40% can still work if the winners are far larger. Win rate alone hides this, which is why I teach expectancy before any strategy tuning.
Mentor suggestion: judge a setup on the sample, never on today’s trade. A single trade can lose even when expectancy is positive, and that is normal.
Expectancy = (Win Rate × Average Gain) − (Loss Rate × Average Loss). Loss rate is 1 minus win rate, and average loss is entered as a positive number. The result is in Rs per trade.
Published trading guides state this same formula, so it is a standard method rather than my own invention. There is also a quick cross-check: add up the net result of all trades and divide by the number of trades. If the two answers differ, something is wrong in your journal.
Count your trades, find the win rate, find the average gain and average loss, then apply the formula and subtract costs. Do it per setup, not for your whole account. Eight rows are enough.
Example (illustrative): Vivek logs 40 trades of one intraday breakout setup on high-volume NSE stocks. He plans to risk Rs 1,200 per trade.
| Step | What you enter | Vivek’s illustrative numbers |
|---|---|---|
| 1 | Total trades in the sample | 40 trades |
| 2 | Winning trades, then win rate | 18 wins ÷ 40 = 45% |
| 3 | Losing trades, then loss rate | 22 losses ÷ 40 = 55% |
| 4 | Average gain per winning trade | Rs 54,000 ÷ 18 = Rs 3,000 |
| 5 | Average loss per losing trade | Rs 26,400 ÷ 22 = Rs 1,200 |
| 6 | Expectancy per trade | (0.45 × 3,000) − (0.55 × 1,200) = Rs 690 |
| 7 | Expectancy in R (R = planned risk) | Rs 690 ÷ Rs 1,200 = 0.575R |
| 8 | After costs (Rs 150 per trade, simplified) | Rs 690 − Rs 150 = Rs 540 = 0.45R |
Chart logic behind the numbers. Vivek’s plan uses a stock at an illustrative price near Rs 1,000. Entry (A): Rs 1,000, when price closes above the morning range high. Confirmation: volume above the recent average on the signal candle. Stop Loss (B): Rs 988, below the range low, so risk is Rs 12 per share. Target (C): Rs 1,030, so reward is Rs 30 per share and the Reward to Risk Ratio is 1 : 2.5. There is no official minimum Reward to Risk Ratio; this is a teaching guideline only.
Position sizing: risk amount ÷ risk per unit = Rs 1,200 ÷ Rs 12 = 100 shares. If the target is hit, the gain is 100 × Rs 30 = Rs 3,000, which is exactly Vivek’s average gain above. For index derivatives, size the same way but check the current lot size on the NSE website.
No-setup condition: no close above A, or no volume expansion, means no trade. Waiting is part of the system.
R is your planned risk on a trade. Vivek’s R is Rs 1,200, so a gain of Rs 3,000 is 2.5R and a full loss is 1R. In R terms:
The advantage of R is that it lets you compare an Rs 500-risk trader with an Rs 5,000-risk trader, or a stock setup with a crude oil setup, on the same scale. It also shows whether your results come from the setup or just from taking larger size.
Break-even win rate = 1 ÷ (1 + Reward to Risk Ratio), before costs. At 1 : 1 you need 50%. At 1 : 2 you need about 33.3%, and at 1 : 3 you need 25%. Costs push the real requirement higher.
| Reward to Risk Ratio | Break-even win rate | Quick check |
|---|---|---|
| 1 : 1 | 50.0% | 50.0% × 1 = 50.0% × 1 |
| 1 : 1.5 | 40.0% | 40.0% × 1.5 = 60.0% × 1 |
| 1 : 2 | 33.3% | 33.3% × 2 = 66.7% × 1 |
| 1 : 3 | 25.0% | 25.0% × 3 = 75.0% × 1 |
Use this table as a quick filter before you backtest. If a setup needs 60% wins at 1 : 1 and your sample shows 45%, you already know the answer.
Because expectancy depends on average gain and average loss as much as on win rate. A trader who wins often but takes small gains and large losses can have a negative number. Small losses and larger gains can work even with a low win rate.
| Trader (illustrative) | Win rate | Average gain | Average loss | Expectancy per trade |
|---|---|---|---|---|
| Ram | 40% | Rs 3,000 | Rs 1,000 | +Rs 600 |
| Shyam | 70% | Rs 1,000 | Rs 2,500 | −Rs 50 |
| Jeevan | 50% | Rs 1,500 | Rs 1,500 | Rs 0 |
| Kartik | 55% | Rs 1,200 | Rs 1,000 | +Rs 210 |
Common mistake: Shyam sells his winners early and holds his losers, which feels comfortable. Practical fix: write down a fixed stop and a target before entry, then log what actually happened. Trading psychology shows up directly in these two averages.
There is no official number. Published guides disagree, with some calling a handful of trades meaningless and others asking for 30 to 100 or more per setup. Pick a rule, write it down, and apply it before you read the result.
The reason is simple: with few trades, one lucky streak can double your average gain. Treat results from a small sample as a draft. When you change any rule of the setup, start a new sample for the changed version.
The formula above is gross. Brokerage, STT, exchange charges, GST, stamp duty and slippage reduce each trade. In Vivek’s example, a simplified Rs 150 per trade moves expectancy from Rs 690 to Rs 540. Your actual costs depend on your broker and instrument, so check current charges on your broker’s and the exchange’s official pages.
For options, the premium can fall to zero, spreads can be wide, and time decay works against buyers. I like trading options in Nifty 50 and prefer options near 0.7 delta with low theta, but that is a personal preference, not a claim of results. Whatever you prefer, log each option setup in its own sample and note that delta, theta and slippage are simplified in any example like this one.
| Common mistake | Practical fix |
|---|---|
| Using win rate alone to judge a setup | Always pair win rate with average gain and average loss. |
| Mixing setups in one sample | Calculate expectancy separately for each setup and time frame. |
| Judging after 8 to 10 trades | Collect a larger sample first; say your rule in advance. |
| Ignoring brokerage, STT, other charges and slippage | Subtract a realistic cost per trade before you read the result. |
| Deleting or skipping bad trades from the journal | Log every trade, including the ones you feel embarrassed about. |
| Moving the stop loss and calling the result a 1 : 3 trade | Measure the result you actually got, not the plan. |
Expectancy describes a sample. It does not give permission to trade every day. Skip the trade, or pause the setup, in these cases:
There is no official number. Anything above zero after costs, over a large enough sample, shows an edge on that sample. Many traders prefer to read it in R and compare it with their largest losing streak.
Expectancy = (Win Rate × Average Gain) − (Loss Rate × Average Loss), where loss rate is 1 minus win rate and average loss is entered as a positive number. The result is the average Rs or R per trade.
Put win rate as a decimal in B1 (45% = 0.45), average gain in B2 and average loss in B3. Then use =(B1*B2)-((1-B1)*B3). For expectancy after costs, subtract your cost per trade in another cell.
Yes. The same formula works for stocks, futures, options and forex, as long as you use results from one setup and one market at a time. Enter average gain and loss in Rs, or in R for cross-market comparison.
Yes. In the illustrative table above, Ram wins 40% of trades, but his average gain is three times his average loss, so his expectancy is +Rs 600 per trade before costs.
No. Reward to Risk Ratio compares one trade’s target distance with its stop distance. Expectancy combines that with how often the setup actually wins.
Yes, if you log each option trade’s actual result in Rs. Theta, delta changes, spreads and the risk of losing the whole premium make options results uneven, so keep a separate sample for each option setup.
Monthly, or after a fixed block of trades per setup. A rolling view of the last 30 to 50 trades shows if the edge is fading.
Count them as trades with a result of about zero, or use the shortcut: total net result ÷ number of trades. Both methods give the same expectancy.
Summary: Win rate tells you how often. Expectancy tells you how much, on average, after you combine it with average gain and average loss. Log every trade of one setup, calculate expectancy in Rs and in R, subtract costs, and wait for a sample you decided on in advance. If the number is zero or negative, fix the setup before you add size. If it is positive, keep the same rules and keep measuring.
Keep learning with more articles on the Trading Direction blog, practise logging trades in the Trading Direction app, or read my trading books for the chart logic behind entries and stops.
The free course covers the foundations behind risk, stops and position size, so the numbers in this article make sense in practice.
Join the Free Trading CourseWe’d Love Your Feedback!
Please take a minute to share your review and Submit Rating.
Search ‘Trading Direction’ on Google or Google Maps, then click Write a Review.
https://share.google/JCfFYqYVsAioCacP4
Thank you!