P&L

Average win versus average loss, honestly

The payoff ratio, why charges hit the two sides differently, and what one giant expiry does to your averages.

2025-11-11 · 6 min read

Divide your average winning trade by your average losing trade and you get the payoff ratio. Below one, your winners were smaller than your losers. Above one, the opposite.

Neither reading is an instruction. Both are bookkeeping — and both get distorted in ways worth knowing.

Charges are not symmetric

A small win can disappear entirely after brokerage and statutory charges, while a small loss simply becomes slightly larger. Compute the ratio on gross and on net and you will often see two different personalities.

Average trade outcome, gross versus net
Average win (gross)₹4kAverage win (net)₹3kAverage loss (gross)₹3kAverage loss (net)₹4k

Payoff drops from 1.24 gross to 0.83 net once charges are applied. Illustrative journal data, not a live book and not a performance claim.

One expiry can own your average

A single ₹2 lakh day next to forty scratch trades will dominate the mean. Medians, or a trimmed mean that drops the extreme 5% on each end, describe a typical trade far better.

Keep the outlier on the calendar. Just do not let it define the average you use for planning.

Do not chase a target ratio

Holding losers longer or cutting winners early will move the ratio and damage the book. If you genuinely change your exit process, date the change and measure forward from there. Back-fitting a new rule onto old trades is how journals turn into fiction.

Mean versus median, same 96 trades
MeasureAverage winAverage lossPayoff
Mean (all trades)₹6,900₹3,4002.03
Mean, excluding one big day₹3,150₹3,4000.93
Median₹2,800₹3,1000.90

One outsized expiry inflated the mean by more than double. Illustrative journal data.

Key takeaways

Your book already has these numbers. Import a broker CSV and the charts above draw themselves from your own closed trades.
Open the journal