A trader who wins 70% of their trades can still blow up their account if they don’t look beyond the win rate — which is exactly why you need a full set of trading metrics, not just one number.

Which trading metric matters most?
No single metric answers every question, but expectancy (the average expected profit/loss per trade) comes closest to answering the core question: “is this strategy sustainably profitable?”

1. Win rate

Formula: number of winning trades ÷ total number of trades.

Win rate is the easiest metric to calculate and also the easiest to be misled by. A strategy that wins 70% of its trades sounds impressive, but if the average loss is 3-4 times larger than the average win, the account still bleeds out over time. Conversely, a strategy that only wins 35% of the time can still be consistently profitable if each winning trade is large enough relative to each losing one. In other words, win rate only answers “how often are you right,” not “are you profitable” — two entirely different questions.

2. Expectancy (average profit/loss per trade)

Formula: (win rate × average win) − (loss rate × average loss).

This should be treated as the central metric in any performance review, since it combines both how often you’re right and the size of each win or loss into a single number. Positive, stable expectancy over multiple weeks signals that a strategy is performing as intended; positive but highly volatile expectancy from week to week points to an execution consistency issue rather than necessarily a flaw in the strategy itself.

3. Risk-reward ratio

Formula: average win ÷ average loss.

Many traders confuse risk-reward ratio with expectancy, but the two concepts complement rather than replace each other. Risk-reward ratio only describes the payoff shape of a trade (how much you gain if you’re right versus how much you lose if you’re wrong), while expectancy also accounts for how often you’re actually right or wrong. A strategy with a 1:3 risk-reward ratio but only a 20% win rate can still have negative expectancy. This is why you shouldn’t rely on just one of these two metrics to decide whether to keep or drop a setup.

4. Maximum drawdown

Formula: the largest drop from peak equity to trough equity, expressed as a percentage or an absolute amount.

Maximum drawdown doesn’t measure profit — it measures a strategy’s real-world tolerance for pain. Two strategies with the same end-of-period profit but one experiencing a 15% drawdown and the other a 40% drawdown represent two completely different levels of risk, even though the final profit number is identical. This is also a metric that prop trading platforms commonly enforce as a hard limit in evaluation rules, since it directly reflects a trader’s capital management discipline.

5. Average holding time

Formula: total time trades were held ÷ number of trades, ideally calculated separately per setup type.

This metric gets little attention but is a strong tool for spotting a mismatch between plan and execution. If a trader identifies as a scalper (holding trades for a few minutes) but their actual average holding time stretches into hours, that’s a sign they’re holding losing trades too long in hopes of a reversal — a common emotional behavior that traders rarely recognize in themselves without looking at the numbers.

6. Trade size deviation (consistency score)

Formula: standard deviation of position size across trades, relative to the average size.

This is a metric few traders track on their own, but many account evaluation firms use it to measure capital management discipline. A trader entering trades with a consistent size across the board shows they’re sticking to their planned risk parameters; sharply fluctuating position sizes — especially a spike right after a losing streak — are usually a sign emotion is driving the decision (trying to “win it back” with a bigger bet).

An example of how a proprietary number could be used here: “among traders removed from the evaluation for violating risk rules, the majority showed a significantly higher trade size deviation than those who passed.” This type of figure needs to come from the platform’s actual aggregated data, reviewed by someone responsible for risk before it’s published.

7. Recovery factor

Formula: net profit ÷ maximum drawdown.

This is the least common metric on the list, but it offers a perspective the other six don’t: how efficiently profit was generated relative to the risk endured to get there. A high recovery factor means a strategy produced large profits relative to the drawdown it went through; a low recovery factor — even with positive end-of-period profit — shows a trader is “trading off” too much volatility to get that result, a way of operating that’s hard to sustain reliably over the long run.

Tracking all 7 without spreadsheet fatigue

Manually calculating all seven of these metrics for every trade, then updating them weekly, is easy to abandon as trading volume grows. This is why tools that automatically aggregate metrics from trading data are gradually replacing manual spreadsheet work, especially for traders who trade at high frequency or manage multiple accounts at once.

Frequently asked questions

How is win rate different from expectancy?
Win rate only measures how often a trade is profitable, without accounting for the size of the wins or losses. Expectancy combines both frequency and size into one number, making it a more accurate reflection of a strategy’s actual profitability.

Is a high win rate a good sign?
Not necessarily. A strategy winning 70% of its trades can still lose money if the average loss is many times larger than the average win. You need to look at win rate and expectancy together to judge properly.

How is risk-reward ratio different from expectancy?
Risk-reward ratio only describes the ratio between the average win and average loss of a trade, without factoring in win/loss frequency. Expectancy accounts for both at once, making it a more comprehensive metric for evaluating a strategy.

What’s considered a good recovery factor?
There’s no fixed threshold that applies to every strategy, since it depends on trading style and timeframe. As a general rule: the higher the recovery factor, the more efficiently profit was generated relative to the risk endured — it’s best to compare a strategy’s recovery factor across different periods rather than against a single absolute number.

Do funded account evaluation platforms check these metrics?
Many account evaluation firms set hard limits on maximum drawdown and track consistency in position sizing as part of their evaluation criteria, alongside profit targets. It’s worth checking the specific rules of each platform, since criteria can vary.