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R-Multiple Distribution

A histogram of the R outcomes of all your trades.
  • X-axis: R ranges
  • Y-axis: the number of trades in each range.
Let’s learn how to read it through the examples below.

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Reading Distribution Shapes

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Pattern 1. A healthy trend follower (40% win rate)

Rmultiple Pattern1
  • Losses cluster around -1R, showing disciplined stop-losses.
  • Profits spread across a range, showing stability.
  • A long tail to the right is the signature of a good strategy.

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Pattern 2. A dangerous counter-trend trader (80% win rate)

Rmultiple Pattern2
  • Most profits cluster in small wins around +1R.
  • Occasional large losses blow up (-4R, -5R).
  • A tail extending to the left is the signature of a risky strategy.

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Pattern 3. A trader with no edge (50% win rate)

Rmultiple Pattern3
  • Trades cluster symmetrically around 0
  • No meaningful tail
  • This means no meaningful profit — effectively just paying fees.
Compare the win rates of patterns 1 and 2 — 40% vs. 80% — and pattern 2 wins by a landslide. But read the graphs and you’ll see that the strategy that makes money long-term is pattern 1.

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4 Statistics You Can Read from the Distribution

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1. Maximum and minimum

The largest profit and largest loss produced by the strategy.

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2. Median

The median profit across all trades with this strategy. The closer the median is to the mean, the healthier the distribution.

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3. Skew

A number showing whether the distribution is symmetric or leans to one side.
  • +0.5 or higher (positive skew): Long right tail → occasional big wins; a healthy shape
  • Near 0: Symmetric → weak or no edge
  • -0.5 or lower (negative skew): Long left tail → occasional big losses; a danger sign

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4. Standard deviation

The volatility of your trade outcomes — the higher it is, the harder results are to predict.

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Outlier Dependence

Outliers are the most extreme values in the distribution — in trading, usually your top 3 trades.

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How it’s calculated

Case 1. Healthy trader A
  • 100 trades, cumulative profit +50R
  • Top 3 trades: +5R + 4R + 3R = 12R
  • Dependence: 24%
  • Even without the best 3 trades, they’re up +38R — the other 97 trades earned +0.39R each on average.
Case 2. Luck-dependent trader B
  • 100 trades, cumulative profit +50R
  • Top 3 trades: +25R + 10R + 5R = 40R
  • Dependence: 80%
  • Remove the best 3 trades and only +10R remains — the other 97 trades averaged +0.1R, barely above break-even.
Both traders have the same cumulative profit of +50R. But A has skill, while B was most likely just lucky.

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How to Improve, by Type

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1. If you have a left tail (big losses)

  • It’s a stop-loss management problem.
  • Check whether you exit at the SL in your journal, and refine your strategy with the goal of minimizing trades beyond -1R.

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2. If you have no right tail

  • It’s an early take-profit problem.
  • Price could run to +2R or +3R but you’re closing before it gets there — check the MFE metric in strategy analysis and push your take-profits later.

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3. If your skew is negative

  • The strategy’s asymmetry itself is bad.
  • You’re collecting small wins while occasionally taking big losses — focus only on trades with a high R/R rather than a high win rate.

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4. If your outlier dependence is high

  • Build a larger sample of trades.
  • At around 50 trades, one or two big trades can dominate the results; past 200 trades, you can see the strategy’s true validity and your real skill.