Open this calculator on its own page
🎯 Expectancy Calculator
E = p·b − (1−p), in units of what you risk. A positive expectancy is not a promise: lesson 19 shows it takes 571 trades before your own record can establish one.
💡 What This Means
Expectancy is your average profit per trade. If positive, you're printing money. If negative, you're mathematically doomed.
Expectancy Is The ONLY Metric That Matters
Forget everything else. Expectancy tells you the average $ you make (or lose) per trade. It's the single number that determines if you're profitable or bankrupt.
💎 The Brutal Truth
Positive expectancy = Money printing machine
Negative expectancy = Slow death by 1,000 cuts
There's no middle ground. The math doesn't care about your feelings.
Real Example: Two Traders, 100 Trades Each
❌ Trader A: Negative Expectancy
- Total Wins: $7,000
- Total Losses: $9,000
- 100 trades
- Expectancy: -$20/trade
After 1,000 trades: -$20,000
That is the average. It says nothing about the order the trades arrive in, and a bad run inside it looks exactly like a good method having a bad month.
✓ Trader B: Positive Expectancy
- Total Wins: $12,000
- Total Losses: $4,000
- 100 trades
- Expectancy: +$80/trade
After 1,000 trades: +$80,000
Also an average, and not a promise. Lesson 19 shows fifty trades cannot tell a method making 0.35R apart from one with no edge at all.
⚠️ Why Most Traders Fail
They track everything EXCEPT expectancy:
- Total P&L (misleading, could be luck)
- Biggest win (irrelevant if you give it back)
- Number of green days (doesn't matter if red days are bigger)
Track expectancy. Nothing else matters.
The Math Behind Expectancy
Expectancy Formula
Expectancy = (Total Wins - Total Losses) / Number of Trades
That's it. Dead simple. Your average profit per trade.
Profit Factor (Supporting Metric)
📊 Profit Factor = Total Wins / Total Losses
Shows how much you make per dollar lost.
- PF < 1.0 = Losing system
- PF = 1.5-2.0 = Profitable system
- PF > 3.0 = Elite system
Example: $12,000 wins / $4,000 losses = 3.0 Profit Factor
Average R-Multiple
If you track risk in R-units (1R = your initial risk per trade):
Average R = Net Profit / (Number of Trades × Risk per Trade)
Normalizes performance across different position sizes.
Target: +0.5R to +1R per trade = professional level
Sample Size Matters
| Number of Trades | Confidence Level |
|---|---|
| <30 | Not statistically significant |
| 30-100 | Marginal confidence |
| 100-300 | Good confidence |
| 300+ | High confidence |
Professional Expectancy Standards
✓ What Your Numbers Should Look Like
Scalping: $5-20 expectancy per trade
Day Trading: $20-100 expectancy per trade
Swing Trading: $100-500 expectancy per trade
Position Trading: $500-2,000+ expectancy per trade
The Expectancy Improvement Framework
Only 2 Ways to Improve Expectancy:
1. Increase average winner
- Let winners run (trail stops)
- Take partials at logical targets
- Better entry timing (improve R:R)
2. Decrease average loser
- Cut losses faster
- Tighter stops at structure
- Skip low R:R setups entirely
Taking Profits Too Early
Most traders cut winners at +1R and let losers run to -1R.
Result: Even with 60% accuracy, expectancy is ZERO.
- Scale out: Take 50% at 2R, let 50% run to 4R+
- Average winner: 3R
- Average loser: -1R
- Result: Positive expectancy even at 40% accuracy
📖 Related Education
For deep dive into expectancy optimization: