Trading Expectancy Explained: Win Rate, Payoff Ratio, and Average R

What Is Trading Expectancy?

Trading expectancy is the average amount you can expect to gain or lose per trade over a large sample. It blends how often you win with how much you typically make when right versus lose when wrong. Positive expectancy suggests your method has an edge; negative expectancy means the approach will likely bleed over time, even if some trades look great.

Think of it like a batting average plus the quality of hits. You don’t need to win every trade; you need your wins and losses to balance out to a positive average over many repetitions.

Expectancy is most useful when you measure it in consistent units. In trading, that unit is often R, which helps you compare results across markets and timeframes.

The Ingredients: Win Rate and Average R (Payoff Ratio)

Win rate is the percentage of trades that close profitably. Average R is the average R-multiple you make or lose per trade.

R (risk unit) is your initial risk per trade, defined as the distance from entry to stop-loss. A profit of +2R means you earned twice your initial risk; a loss of -1R means your stop was hit.

Average R captures both your reward and your risk in one number. It’s closely related to payoff ratio, which is the average win size divided by the average loss size. For example, if winners average +2R and losers average -1R, your payoff ratio is 2:1 and your average R across all trades depends on how often you win versus lose.

Expectancy grows when either your win rate improves or your average R improves (larger wins, smaller losses), ideally both. A strategy with a modest win rate can still be profitable if average R is high. Conversely, a high win rate can still be unprofitable if rare losses are much larger than typical wins.

Simple Examples to Build Intuition

Example 1: You take 10 trades. Four winners make +2R each; six losers lose -1R each. Total = (4 × +2R) + (6 × -1R) = +2R. Your average per trade is +0.2R, a positive expectancy.

Example 2: You win 7 of 10 trades, but winners average +0.5R and the three losses are -2R each. Total = (7 × +0.5R) + (3 × -2R) = +3.5R - 6R = -2.5R. Despite a 70% win rate, expectancy is negative.

Example 3: You win 3 of 10 trades with big runners averaging +3R, and lose 7 at -1R. Total = (3 × +3R) + (7 × -1R) = +9R - 7R = +2R. Low win rate, but positive expectancy due to strong average R.

These scenarios show why tracking both win rate and average R matters. It’s not just how often you win, but how much you win when right compared with how much you lose when wrong.

How to Measure and Improve Expectancy

• Log every trade in R. Record entry, stop, exit, and the R-multiple result. Over 30–100 trades, your average will stabilize.
• Protect the downside. Tighten sloppy stops, cap slippage, and avoid oversized losses; a few large negatives can erase many wins.
• Let winners breathe selectively. When conditions favor trend continuation, scale out or trail stops to lift average R without forcing every trade to run.
• Focus entries. Cleaner entries near defined levels can reduce initial risk distance, improving R even if raw price targets don’t change.
• Test adjustments safely. Use a simulator to rehearse refinements quickly before applying them live. See our guide: How to Practice Trading Without Risk.

To track progress, periodically compute your win rate and average R from your log. If one weakens, adjust specific behaviors: reduce avoidable losses, refine exits to capture more of the move, or skip marginal setups to raise quality.

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