Understanding R-Multiples: A Complete Guide

R-multiples are one of the most powerful concepts in trading analytics. This guide explains what they are, why they matter, and how to use them effectively.

What is an R-Multiple?

An R-multiple expresses your trade outcome in terms of your initial risk (R). If you risked $100 on a trade:

This standardization allows you to compare trades across different instruments, position sizes, and account sizes.

Why R-Multiples Matter

1. Objective Performance Comparison

Without R-multiples, a $500 profit on AAPL and a $500 profit on AMZN might seem equal. But if you risked $250 to make $500 on AAPL (2R) and risked $1000 to make $500 on AMZN (0.5R), the AAPL trade was clearly better risk-adjusted performance.

2. Calculating Expectancy

Your trading system's expectancy is:

Expectancy = (Win Rate × Average Win R) + (Loss Rate × Average Loss R)

Example:

A positive expectancy means you have an edge.

3. Position Sizing

Once you know your expected R per trade, you can optimize position sizing:

How Practice—Process Calculates R-Multiples

When you log a trade, we calculate R-multiples using:

R-Multiple = (Exit Price - Entry Price) ÷ (Entry Price - Stop Loss)

For short trades: R-Multiple = (Entry Price - Exit Price) ÷ (Stop Loss - Entry Price)

The R-Multiple Distribution

Your R-multiple distribution reveals important patterns:

Healthy Distribution

Problematic Distribution

Using R-Multiples in Practice—Process

Navigate to Analytics → R-Multiple Analysis to see:

Advanced: Risk-Adjusted Returns

Once you think in R-multiples, you can evaluate:

Common Mistakes