P&L tells you what happened. R-Multiple tells you whether you have an edge. SQN tells you how strong it is. Kelly tells you how much to risk. This is the framework serious traders use.
Before you enter a trade, you define your stop loss — the point where you're wrong. The distance from entry to stop, expressed in dollars, is 1R. Every trade result is then measured as a multiple of that: +2.4R means you made 2.4x your risk. −0.8R means you closed before your stop and lost less than planned.
This matters because P&L is meaningless without context. A $500 win on a 0.1-lot position is +5R — a great trade. A $500 win on a 1.0-lot position is +0.5R — a mediocre one. Tracking P&L treats these the same. R tracks the quality of your decisions, not the scale of your bets.
Expectancy — the average R per trade across your sample — is the number that matters most. A positive expectancy means your system makes money over time. A negative expectancy means no amount of position sizing saves you. Know your expectancy before you scale.
The same $500 win — different edges
0.1 lot · $100 risk (1R)
$500 win
+5.0R
Excellent trade
1.0 lot · $1,000 risk (1R)
$500 win
+0.5R
Mediocre trade
Same P&L. Completely different edges. R sees the difference.
Expectancy formula
45% win rate · +2.5R avg win · 0.9R avg loss
E = +0.63R per trade ✓
55% win rate · +1.0R avg win · 1.2R avg loss
E = −0.04R per trade ✗
Expectancy tells you if you make money per trade. SQN tells you how confident to be in that number. Kelly tells you how much to risk.
System Quality Number — Van Tharp method
A 0.5R expectancy with high variance is less reliable than a 0.3R expectancy with tight consistency. SQN captures both: expectancy divided by its standard deviation, scaled by sample size. More trades, tighter variance, higher expectancy — all push SQN up.
Optimal risk per trade from your own statistics
Kelly Criterion uses your actual win rate and reward-to-risk ratio to calculate the mathematically optimal fraction of capital to risk per trade. It's not a generic "1% rule" — it's calibrated to your specific edge. As your live journal data grows, SignalDeck updates Kelly automatically.
Example: 45% win rate, 2.5R avg win, 0.9R avg loss
Updates live as your journal data grows. No manual recalculation.
SignalDeck doesn't ask you to calculate any of this manually. Connect your MT5 broker — trades import automatically. Add your stop loss to each imported trade — R-Multiple, expectancy, SQN, and Kelly are calculated instantly and update with every new trade you add.
The dashboard breaks down your edge by instrument, session, day of week, and setup tag. A strategy that works on EURUSD might underperform on GBPUSD. A session edge on London open might decay by New York close. R-analytics surface these patterns in your actual data — not theoretical curves.
Expectancy
+0.47R
SQN Score
2.4
Win Rate
43.8%
Kelly (half)
3.9%
Edge by session
Asian session is destroying your edge — stop trading it.
What is R-Multiple in trading?
R-Multiple expresses every trade result as a multiple of your planned risk (1R). If you risk $100 and make $240, the result is +2.4R. R normalizes all trades to the same unit regardless of position size, instrument, or dollar amount — making your edge measurable across strategies and account sizes.
What is SQN score?
SQN (System Quality Number) measures the quality of a trading system by combining expectancy and its consistency. Scores below 1.6 indicate a weak system, 2.0–3.0 is good, and above 3.0 is excellent. SQN is more meaningful than win rate alone because it accounts for how consistent the edge is, not just the average return per trade.
Why is R-Multiple better than tracking P&L?
P&L varies with position size. A $500 win on a 0.1-lot trade (+5R) and a $500 win on a 1.0-lot trade (+0.5R) represent completely different edges. Tracking P&L treats them the same. R normalizes all trades to the same quality scale so your expectancy and edge metrics are accurate regardless of how aggressively you're trading.
How does Kelly Criterion work?
Kelly Criterion calculates the optimal fraction of capital to risk per trade based on your actual win rate and reward-to-risk ratio. SignalDeck calculates Kelly from your live journal data and updates it as your statistics evolve. Most traders use half-Kelly to reduce variance while still sizing toward their actual edge.
R-Multiple on every trade, live expectancy, SQN scoring, Kelly Criterion position sizing, and Walk-Forward Analysis for strategy validation — all from your actual trade history.
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