A cross-asset conceptual guide to the two metrics that define whether a trading system actually makes money — how expectancy measures average dollars per trade, how profit factor measures gross win versus gross loss, and why both beat win rate.
Key Takeaways
- Expectancy is the average dollar amount you expect to make (or lose) per trade over many trades.
- Profit factor is gross profit divided by gross loss — anything above 1.0 is profitable, above 1.5 is strong.
- Both metrics combine win rate and reward-to-risk into a single measure of system quality.
- A high win rate with poor R:R can have negative expectancy; a low win rate with strong R:R can be highly profitable.
- Expectancy must be positive after costs (spread, commission, slippage) for a system to survive in the real world.
Beyond Win Rate
New traders obsess over win rate — the percentage of trades they win. But win rate in isolation is meaningless. A system that wins 90% of the time risking 2 to make 1 is unprofitable; a system that wins 35% of the time risking 1 to make 4 is highly profitable. The metrics that actually determine profitability are expectancy and profit factor, because they combine win rate with the size of wins and losses into a single measure of system quality.
Key Takeaways
- Expectancy = average dollar per trade, combining win rate and win/loss size.
- Profit factor = gross profit ÷ gross loss; above 1.0 is profitable.
- Both reveal system quality that win rate alone hides.
Expectancy
Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss). A system winning 40% of trades with an average win of $300 and average loss of $100 has expectancy = (0.40 × $300) − (0.60 × $100) = $120 − $60 = +$60 per trade.
Expectancy tells you the expected dollar result of one average trade. A positive expectancy means the system makes money over many trades; a negative expectancy means it loses. The power of expectancy is that it works for any combination of win rate and payoff — it reduces every system to a single comparable number.
Profit Factor
Profit Factor = Gross Profit ÷ Gross Loss (over a sample of trades). A system with $12,000 of winning trades and $6,000 of losing trades has a profit factor of 2.0. Above 1.0 is profitable; above 1.5 is solid; above 2.0 is excellent.
Profit factor is a ratio, not a per-trade number, which makes it useful for comparing systems independent of position size. A profit factor of 1.0 is break-even; below 1.0 loses money. Professional systems often target a profit factor of 1.5–2.5 — high enough to survive costs and drawdowns, realistic enough to be achievable.
| Profit Factor | Interpretation |
|---|---|
| < 1.0 | Losing system |
| 1.0 – 1.2 | Marginal; costs likely erase it |
| 1.2 – 1.5 | Modestly profitable |
| 1.5 – 2.0 | Solid, robust edge |
| > 2.0 | Excellent (and rare in practice) |
How Win Rate and R:R Combine
Expectancy and profit factor both derive from the same two inputs: win rate and reward-to-risk. Use the TradeRiskMath expectancy calculator to plug in your system’s win rate, average win, and average loss and see the resulting expectancy and profit factor — before you risk real capital on an unproven system.
| Win Rate | Avg Win : Avg Loss | Expectancy (per $100 risked) | Verdict |
|---|---|---|---|
| 90% | $50 : $100 | $45 − $10 = +$35 | Profitable but fragile |
| 40% | $300 : $100 | $120 − $60 = +$60 | Solidly profitable |
| 35% | $400 : $100 | $140 − $65 = +$75 | Strongly profitable |
| 55% | $100 : $100 | $55 − $45 = +$10 | Barely profitable |
The Cost Reality Check
Every expectancy figure must be calculated after costs — spread, commission, and slippage. A system with +$60 gross expectancy that pays $15 per trade in costs has +$45 net expectancy. A system with +$10 gross expectancy and $15 in costs is actually a loser. Thin edges die on costs; this is why execution quality and instrument liquidity matter as much as the signal.
Sample Size and Reliability
- A positive expectancy over 20 trades proves almost nothing — variance dominates.
- A positive expectancy over 200+ trades is meaningful evidence of an edge.
- Profit factor below 1.3 over a large sample is fragile — costs or regime change can flip it negative.
- Re-test expectancy after major market regime changes; edges decay.
Common Mistakes
- Quoting win rate without R:R — the two are meaningless apart.
- Computing expectancy before costs — gross expectancy hides the real result.
- Trusting expectancy from a small sample — variance creates illusionary edges.
- Chasing a higher profit factor by over-fitting — a 5.0 profit factor in backtest usually means curve-fitting, not a real edge.
Frequently Asked Questions
What is a good expectancy?
Any positive net expectancy (after costs) is good. The absolute number depends on your risk per trade and frequency — a +$60 expectancy on 1% risk taken 200 times a year is excellent; the same expectancy taken 10 times a year is modest.
What is a good profit factor?
Above 1.5 is solid and realistic; above 2.0 is excellent. Be suspicious of backtested profit factors above 3.0 — they usually indicate over-fitting rather than a durable edge.
Can a low win rate be profitable?
Yes, if the reward-to-risk is high enough. A 35% win rate at 1:4 R:R has strong positive expectancy. Trend-following systems routinely profit with win rates below 40%.
The Bottom Line
Expectancy and profit factor are the two metrics that actually determine whether a trading system makes money, because they combine win rate with the size of wins and losses into a single measure of quality. Expectancy gives the average dollar per trade; profit factor gives the gross win-to-loss ratio. Both must be positive after costs and measured over a large enough sample to be trusted. Master these numbers and you evaluate systems by their true edge — not by the seductive but meaningless win rate that misleads most new traders.
Educational Disclaimer
This article is provided strictly for educational purposes and does not constitute financial, investment, or trading advice. Trading stocks, options, futures, forex, and crypto involves substantial risk of loss. Always evaluate trades against your own financial situation and risk tolerance, and consult a licensed professional before making investment decisions. Past performance does not guarantee future results.