Analyzing Your Trading Performance: The Metrics That Matter

You had a green month. Good news, right?

Maybe. Or maybe you got lucky, took excessive risk, and your strategy is actually broken. A single number—profit or loss—doesn't tell you much.

To really understand your trading, you need to track the metrics that reveal what's actually happening. This isn't about being a data nerd. It's about catching problems before they blow up your account and recognizing when your edge is working.

The Core Metrics

Win Rate

What it is: The percentage of trades that are profitable.

Win Rate = (Winning Trades / Total Trades) x 100

What it tells you:

• How often you're right
• Whether your entries are well-timed
• If combined with other metrics, whether your strategy type is working

What it doesn't tell you:

• Whether you're actually making money (a 90% win rate with tiny wins and huge losses loses money)
• The quality of your edge

Benchmarks:

• Trend-following: 30-45% is normal
• Mean reversion: 55-65% is normal
• Scalping: 50-60% is normal

Don't chase high win rates. Some of the best strategies in history had 40% win rates but massive profit factors.

Average Win vs. Average Loss (R-Multiple)

What it is: The ratio of your average winning trade to your average losing trade.

R-Multiple = Average Win / Average Loss

What it tells you:

• Your risk-reward profile
• Whether winners are big enough to overcome losers
• The sustainability of your edge

What it doesn't tell you:

• Whether you're making money (an R-multiple of 3 with 20% win rate loses money)

Benchmarks:

• R-multiple of 1.5+ with win rate above 40% = solid
• R-multiple of 1.0 requires win rate above 50% to be profitable
• R-multiple below 1.0 requires very high win rate to work

Profit Factor

What it is: Total gross profit divided by total gross loss.

Profit Factor = Gross Profit / Gross Loss

What it tells you:

• Your overall edge in a single number
• How much you make for every dollar you lose
• Whether your strategy has positive expectancy

Benchmarks:

• Below 1.0: You're losing money
• 1.0-1.2: Marginal edge, probably not sustainable after costs
• 1.2-1.5: Decent edge, workable
• 1.5-2.0: Good edge
• Above 2.0: Excellent (or you haven't traded enough size for results to normalize)

Profit factor is one of the best single metrics because it captures both win rate and average win/loss in one number.

Expectancy (Expected Value per Trade)

What it is: The average amount you expect to make (or lose) on each trade.

Expectancy = (Win Rate x Average Win) - (Loss Rate x Average Loss)

What it tells you:

• Your dollar edge per trade
• Whether taking more trades helps or hurts
• The mathematical expectation of your system

Example:

• Win rate: 45%
• Average win: $300
• Average loss: $200
• Expectancy = (0.45 x $300) - (0.55 x $200) = $135 - $110 = $25 per trade

A $25 expectancy means over many trades, you expect to make $25 per trade on average. At 10 trades per day, that's $250 expected daily profit.

Maximum Drawdown

What it is: The largest peak-to-trough decline in your account equity.

What it tells you:

• The worst losing streak you've experienced
• How much pain your strategy produces
• Whether you're appropriately sized

Why it matters:

Maximum drawdown is what kills accounts and blows evaluations. You can have positive expectancy but if your drawdown exceeds your risk tolerance (or your prop firm's limits), you lose.

Benchmarks:

• Below 10%: Very conservative
• 10-20%: Moderate
• 20-30%: Aggressive
• Above 30%: Dangerous for most traders

Always assume your future max drawdown will exceed your historical max drawdown. If you can't survive that, reduce size.

Secondary Metrics Worth Tracking

Sharpe Ratio

Risk-adjusted return. Higher is better. Above 1.0 is decent, above 2.0 is excellent. Useful for comparing strategies with different risk levels.

Calmar Ratio

Annual return divided by max drawdown. Shows return per unit of pain. Higher is better.

Average Hold Time

How long you're in trades. Useful for understanding if you're getting out too early (short hold times with winners) or too late (long hold times with losers).

Win/Loss Streaks

Track your longest winning and losing streaks. This helps with psychological preparation and sizing decisions. If you know a 7-trade losing streak is possible, you won't panic when it happens.

Profit by Time of Day

When are you making money? When are you losing it? This can reveal edge decay during certain hours or conditions.

Profit by Day of Week

Some strategies perform differently on different days. Mondays and Fridays often behave differently than mid-week.

How to Use This Data

Regular Review Schedule

Daily: Glance at P&L and any execution issues. Don't overthink.

Weekly: Review win rate, profit factor, and any notable trades. Look for patterns.

Monthly: Full analysis of all metrics. Compare to historical averages. Identify areas for improvement.

Quarterly: Deep dive. Is your edge persisting? Are market conditions changing? Do you need to adjust?

Identifying Problems

High win rate but still losing money:

Your average loss is too big relative to average win. Tighten stops or improve exit timing on losers.

Low win rate and losing money:

Either your entry timing is off or your winners aren't big enough. Analyze losing trades—are they mostly timing issues or idea issues?

Good metrics but still underperforming:

Check execution. Slippage, missed fills, and trading costs might be eating your edge. Compare backtest performance to live performance.

Metrics changed recently:

Market conditions might have shifted. Your strategy edge might be decaying. Don't panic, but investigate.

Setting Realistic Expectations

Use your metrics to forecast reasonable outcomes:

Expected monthly return = Expectancy x Average trades per month

If your expectancy is $25 per trade and you take 200 trades per month, expected return is $5,000. But this is expected value—actual returns will vary.

Realistic range = Expected return +/- (Max drawdown x 2)

You might make $8,000. You might lose $3,000. Both are within normal variance even if your edge is real.

Common Mistakes in Performance Analysis

Not Enough Data

50 trades isn't statistically significant. Neither is 100. You need hundreds of trades before you can draw reliable conclusions about your edge.

Don't make major strategy changes based on small sample sizes.

Ignoring Context

A 60% win rate during a trending market might become 40% during a ranging market. Your metrics exist in a context. When conditions change, expect metrics to change too.

Curve-Fitting to Past Data

You notice your strategy does better on Tuesdays. So you add a "only trade Tuesday" rule. Next month, Tuesday underperforms.

Be very careful about adding rules based on historical quirks. Most patterns in small samples are noise.

Focusing on P&L Only

P&L is the ultimate scorecard, but it's a lagging indicator. By the time your P&L shows a problem, the problem has already cost you money.

Leading indicators—win rate changes, average win shrinking, more losing streaks—can alert you to problems earlier.

Building Your Performance Dashboard

At minimum, track these weekly:

• Total P&L
• Number of trades
• Win rate
• Profit factor
• Average win and average loss
• Largest winner and largest loser
• Current drawdown from peak

Add more metrics as you become comfortable. But don't let data collection become a distraction from actual trading.

The Mindset Shift

Most traders look at their results as a report card. Good month = I'm smart. Bad month = I'm dumb.

Better approach: Your results are data about your system, not judgments about you.

A losing month with solid process execution is better than a winning month with sloppy execution. The winning month might have been luck. The losing month might have been variance.

Track the metrics. Follow the data. Adjust when the evidence supports adjustment, not when emotions demand it.

Over time, you'll develop an intuition for what your strategy should be doing. Deviations from that baseline become obvious. Problems get caught early. Improvements get validated.

That's the real value of performance analysis: not knowing if you made money (you can just check your account balance), but knowing why and whether you can expect it to continue.