Trading Strategy Statistics: Win Rate, Expectancy, Profit Factor & Drawdown
Learn how to measure the performance of a trading strategy using win rate, average winner, average loser, expectancy, profit factor, drawdown, losing streaks and other statistics that reveal whether a strategy actually has an edge.
A 75% win rate sounds impressive.
But what if the average winner makes 0.5R and the average loser loses 3R?
A 40% win rate sounds weak.
But what if the average winner makes 3R while the average loser loses only 1R?
In this lesson, we take the backtest data from Lesson 2 and turn it into meaningful performance statistics.
What You’ll Learn
Why Trading Statistics Matter
Traders naturally remember dramatic wins and painful losses.
Statistics prevent those memorable trades from controlling your judgment.
Large Sample → Evidence
A strategy should be evaluated across a meaningful sample rather than by the outcome of the last few trades.
The Core Strategy Statistics
How often trades win.
Average profit on winning trades.
Average loss on losing trades.
Expected average result per trade.
Gross profit versus gross loss.
Decline from peak equity.
Statistic #1: Win Rate
Win rate measures the percentage of trades that finish as winners.
The Win-Rate Trap
Traders often assume a higher win rate automatically means a better strategy.
It does not.
| Strategy | Win Rate | Avg Winner | Avg Loser |
|---|---|---|---|
| Strategy A | 75% | +0.5R | -2R |
| Strategy B | 40% | +3R | -1R |
Loss Rate
If you exclude breakeven trades, loss rate can often be calculated as:
Loss rate = 46%
Statistic #2: Average Winner
Average winner measures the average size of all profitable trades.
Winning trades: 54
Average winner = +2R
Statistic #3: Average Loser
Average loser measures the average size of losing trades.
Losing trades: 46
Average loser = -1R
Statistic #4: Payoff Ratio
The payoff ratio compares the average winning trade with the average losing trade.
Average loser = 1R
Payoff ratio = 2.0
Statistic #5: Expectancy
Expectancy is one of the most important statistics in strategy analysis.
It estimates the average amount a strategy earns or loses per trade over a large sample.
What Does +0.62R Expectancy Mean?
It does not mean every trade earns 0.62R.
Individual trades may lose 1R, win 2R or finish near breakeven.
Negative Expectancy
Break-Even Win Rate
Break-even win rate tells you approximately how often a strategy must win to avoid losing money given a fixed reward-to-risk relationship.
| Reward : Risk | Approx. Break-Even Win Rate |
|---|---|
| 1 : 1 | 50% |
| 1 : 1.5 | 40% |
| 1 : 2 | 33.3% |
| 1 : 3 | 25% |
This helps explain why a lower-win-rate strategy can still be profitable when winners are substantially larger than losers.
Statistic #6: Profit Factor
Profit factor compares the total amount won with the total amount lost.
Gross losing trades = 46R
Profit factor = 2.35
Interpreting Profit Factor
| Profit Factor | General Interpretation |
|---|---|
| Below 1.0 | Gross losses exceed gross profits |
| 1.0 | Approximately break-even before costs |
| Above 1.0 | Gross profits exceed gross losses |
| Higher Values | Potentially stronger historical efficiency, but sample size and robustness still matter |
Statistic #7: Net R
Net R adds the result of every trade together.
Total losing R = -46R
Net result = +62R
Statistic #8: Average R Per Trade
Trades = 100
Average = +0.62R per trade
With simple win/loss outcomes, this should align with the expectancy calculation.
Statistic #9: Maximum Drawdown
Maximum drawdown measures the largest decline from a previous equity peak to a later trough during the test.
Why Maximum Drawdown Matters
Two strategies can produce the same total profit but require very different emotional and financial tolerance.
Net: +40R
Max drawdown: -6R
Net: +40R
Max drawdown: -22R
Same historical profit. Very different risk journey.
Drawdown in Percentage Terms
If your risk is fixed as a percentage of the account, an R-based drawdown can be translated approximately into account risk.
Historical max drawdown = -10R
Approximate simple drawdown = -5% before compounding effects.
Statistic #10: Maximum Losing Streak
Maximum losing streak measures the largest number of consecutive losing trades in the sample.
Maximum Winning Streak
Winning streaks matter too because they can influence psychology and create unrealistic expectations.
Eight consecutive winners do not mean the ninth trade becomes safer.
Statistic #11: Equity Curve
An equity curve plots cumulative strategy results in chronological order.
The shape of the curve can reveal periods of strong performance, stagnation and drawdown.
Do Not Expect a Perfectly Smooth Equity Curve
Statistic #12: Recovery Factor
Recovery factor compares total return with maximum drawdown.
Maximum drawdown = 8R
Recovery factor = 5.0
Statistic #13: Trade Frequency
Trade frequency affects how quickly a strategy can build a meaningful sample and how practical it is for the trader.
A strategy that averages three trades per month may require much more patience than one averaging three trades per day.
Statistic #14: Average Trade Duration
Duration matters because it affects execution style, overnight exposure and the trader’s lifestyle.
Average hold: 40 minutes
Average hold: 2.5 days
Segment the Data
Overall results can hide important differences.
Example: Same Strategy, Different Sessions
| Session | Trades | Win Rate | Expectancy | Net R |
|---|---|---|---|---|
| London | 70 | 57% | +0.64R | +44.8R |
| New York | 68 | 43% | +0.11R | +7.5R |
Both may be historically profitable, but one session appears substantially stronger.
Example: High Win Rate, Poor Strategy
The strategy wins often but loses more on average than its winners can recover.
Example: Low Win Rate, Positive Strategy
Strategy Statistics Must Fit the Trader Too
A mathematically profitable strategy may still be difficult for a particular trader to execute.
Can require tolerating long losing streaks and waiting patiently for larger winners.
May feel psychologically easier but can be vulnerable if occasional losses are too large.
Sample Size Changes How Much You Can Trust the Statistics
Look for Robustness, Not Perfection
A strategy is more interesting when positive behavior survives across different periods and reasonable variations.
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