Most traders who open a trade journal for the first time look at one number before any other: the win rate. It feels intuitive. A higher share of winning trades sounds like better trading. On its own, though, the win rate says nothing about how much you make when you are right or how much you lose when you are wrong. This article explains three core statistics, shows how they fit together, and uses simple hypothetical numbers to show why win rate alone can mislead you.
What each number actually measures
Win rate is the percentage of closed trades that ended in profit. If 6 out of 10 trades were winners, the win rate is 60%. It tells you how often you were right, not by how much.
Average win and average loss show the typical size of your results. Add up all winning trades and divide by the number of wins. Do the same for losing trades. Comparing the two gives you the payoff ratio. If your average win is twice your average loss, the ratio is 2.
Profit factor is gross profit divided by gross loss. A profit factor above 1 means your winners added up to more than your losers over the period. Below 1 means the opposite. It combines how often you win and how big your wins and losses are into a single figure.
Why a high win rate can still lose money
Consider two hypothetical traders. The numbers are examples for illustration only. Each closed 10 trades.
- Example trader A: 7 wins averaging +20 USDT and 3 losses averaging −60 USDT. Win rate 70%. Gross profit 140, gross loss 180. Net result −40 USDT, profit factor about 0.78.
- Example trader B: 4 wins averaging +75 USDT and 6 losses averaging −25 USDT. Win rate 40%. Gross profit 300, gross loss 150. Net result +150 USDT, profit factor 2.0.
Trader A wins far more often and still ends the period in the red. The losing trades are three times larger than the winning ones, so a few losses erase many small gains. A common way to end up in this position is to take profits quickly while giving losing positions more room, for example by moving or removing a stop-loss. Each habit can feel reasonable trade by trade. The journal shows what they add up to.
Reading the three numbers together
A useful check is the break-even win rate. It is the win rate needed to neither gain nor lose, given your average win and loss. It equals average loss divided by the sum of average win and average loss.
- Example trader A: 60 ÷ (20 + 60) = 75%. Their actual 70% falls short.
- Example trader B: 25 ÷ (75 + 25) = 25%. Their actual 40% is above it.
You can also estimate expectancy, the average result per trade. Multiply win rate by average win, then subtract loss rate multiplied by average loss. For trader A that is 0.7 × 20 − 0.3 × 60 = −4 USDT per trade. For trader B it is 0.4 × 75 − 0.6 × 25 = +15 USDT per trade. Neither figure predicts the future. It only describes what the past sample looked like.
Habits that make your statistics more honest
- Include costs. Trading fees and funding payments reduce every result. Small average wins are hit hardest by them.
- Mind the sample size. Ten or twenty trades can swing sharply on one outlier. Treat early statistics as rough and look at how they change over time.
- Split the data. Compare results by coin and by long versus short. An overall profit factor can hide one area that keeps draining the account.
- Watch the largest losses. A single oversized loss can distort both average loss and profit factor. Ask whether it followed your own plan.
- Do not chase win rate. Changing your exits just to win more often can shrink average wins and grow average losses. The overall picture can then get worse.
Keep in mind that leveraged futures trading carries a high risk of loss, and no statistic removes that risk.
These numbers are only as useful as the data behind them, and tracking them by hand is easy to skip. The BitMe crypto trading journal builds win rate, profit factor, drawdown and results by coin and direction automatically from your closed USDT/USDC futures trades on Bybit, OKX and BloFin. That way you can review them regularly instead of guessing.