Reading results 1: win rate and why it can lie
Win rate alone is one of the most misleading backtest numbers. Learn why you have to read it next to R, average win, average loss, and expectancy to know if a strategy actually makes money.
Part of the Backtesting and Research track on Agenticks. About 11 minutes, written for a advanced reader.
When a backtest finishes, the first number most people look at is the win rate: the percentage of trades that ended profitable. It feels like the headline. A strategy that wins 70 percent of the time sounds far better than one that wins 40 percent. That instinct is exactly where a lot of people get fooled. Win rate is one of the easiest numbers to read and one of the easiest to misread, because on its own it tells you nothing about whether the strategy actually made money.
Every trade has two parts that matter: how often you win, and how much you win or lose when you do. Win rate only covers the first part. To know if a strategy is profitable you also need the average win and the average loss. A high win rate with small wins and large losses can bleed an account dry. A low win rate with large wins and tightly controlled losses can be very profitable. The percentage by itself cannot tell those two cases apart.
Win rate is half a ledger
Think of results as two columns: how often, and how much. Win rate is the first column. Average win and average loss are the second. Reading the first column without the second is like judging a business by how many sales it made while ignoring whether each sale made or lost money.
Traders make the "how much" part comparable using an R-multiple. R is the amount you risked on a trade, your initial stop distance in dollars. A trade that makes twice what it risked is a plus two R win. A trade that hits its stop is a minus one R loss. Measuring results in R instead of raw dollars lets you compare a small trade and a large trade on the same scale, and it makes the relationship between win rate and reward obvious.
Here is the trap in numbers. Strategy A wins 80 percent of its trades, but every winner makes 0.5 R and every loser costs 1 R. Over 100 trades that is 80 wins at plus 0.5 R (plus 40 R) and 20 losses at minus 1 R (minus 20 R), for plus 20 R total. Now Strategy B wins only 40 percent, but winners make 3 R and losers cost 1 R. That is 40 wins at plus 3 R (plus 120 R) and 60 losses at minus 1 R (minus 60 R), for plus 60 R total. The lower win rate made three times as much. The headline number pointed at the wrong strategy.
Strategy A wins 80% of trades but each win is +0.5R and each loss is -1R. Strategy B wins 40% of trades but each win is +3R and each loss is -1R. Over 100 trades, which made more, and why? Strategy B, because its wins are large enough that a low win rate still nets more R B nets +60R (40 wins x 3R minus 60 losses x 1R) versus A's +20R. The size of the average win, not the win rate, did the heavy lifting.
Every win rate has a breakeven reward
If your average win equals your average loss (a 1 R reward), you need to win more than half your trades to come out ahead. If your average win is 3 R against a 1 R loss, you can lose most of your trades and still profit. The win rate that is good enough depends entirely on the reward-to-risk size, so the two numbers only mean something together.
The number that ties it all together is expectancy: the average amount you would expect to win or lose per trade over many trades, given your win rate and the size of your wins and losses. A rough version is (win rate x average win) minus (loss rate x average loss). Positive expectancy means the math leans in your favor across a large sample. Negative expectancy means it does not, no matter how comforting the win rate looks. Expectancy is the single number that survives the win-rate illusion, which is why the next lesson is built around it.
- Win rate
- The percentage of trades that ended profitable
- Average win
- The typical size of a profitable trade
- Average loss
- The typical size of a losing trade
- R-multiple
- A result expressed as a multiple of the risk taken
- Expectancy
- The average win or loss expected per trade
win rate loss win expectancy
Read three numbers, not one
When a test finishes, never stop at the win rate. Read it next to the average win and the average loss, then let expectancy settle the argument. If those numbers are missing, you do not yet know whether the strategy makes money, only how often it happened to be right.
Put the metrics in the order you should read them to judge a strategy honestly.
- Note the win rate as a starting point
- Compare the average win against the average loss
- Express results in R to put trades on one scale
- Let expectancy settle whether the edge is real
You can now see past the win rate
You know why win rate lies on its own, how R-multiples make reward comparable, and why expectancy is the number that actually decides whether a strategy's math has an edge.
Common questions
- Is a high win rate good?
- Not on its own. A strategy can win 80 percent of its trades and still lose money if the losers are much larger than the winners. Win rate only means something once you also know the average win and the average loss.
- What should I read instead of win rate?
- Read win rate together with the average win, the average loss, and expectancy. Expectancy combines how often you win with how much you win or lose into the average result per trade, which is the number that tells you whether the math leans in your favor.
- What is R in trading results?
- R is your initial risk on a trade. An R-multiple expresses each result as a multiple of that risk, so a trade that makes twice what it risked is plus two R and a trade that hits its stop is minus one R. Measuring in R lets you compare trades of different sizes on one scale.
Terms defined in this lesson
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