Trading Expectancy CalculatorExpected Value & Statistical Significance

The only formula that decides if you make money

Every trading strategy reduces to one number. Not the win rate you quote, not your best week — the average R you make per trade across everything you take:

expectancy = (win rate × avg win R) − (loss rate × avg loss R)

R is your risk unit: if you risk $200 on a trade and make $300, that's a 1.5R win. Working in R instead of dollars makes results comparable across different position sizes and account stages — and it makes the math honest, because a $900 winner taken at triple size isn't a better trade than a $300 winner at normal size.

A trader with a 55% win rate, 1.5R average winners and 1R average losers earns 0.55 × 1.5 − 0.45 × 1 = 0.375R per trade. At three trades a day, that's about 1.1R of expected profit daily. Negative expectancy at any win rate means the strategy bleeds — no position sizing scheme can fix it.

Win rate is the most overrated number in trading

Win rate only means something next to payoff size. The same 55% win rate is a losing strategy with 0.7R winners and a strong one with 2R winners. Here is expectancy across the grid (assuming 1R average losses):

Two practical consequences. First, a 45% win rate is perfectly tradeable if your winners run — many trend and breakout strategies live in that row. Second, the fastest way to ruin a good strategy is to cut winners early: moving from 1.5R to 1.0R average winners at a 55% win rate erases three quarters of the edge.

When is your edge statistically real?

Twenty trades of green tells you almost nothing. Trade results are noisy, and the noise is large relative to the signal: a typical intraday strategy has an R standard deviation around 1.2–1.5, while the edge itself might be 0.2–0.4R. To distinguish your expectancy from zero with reasonable (roughly 95%) confidence, you need on the order of:

trades needed ≈ (2σ ÷ expectancy)²

With σ = 1.3R, a 0.3R edge needs about 75 trades to separate from luck. A 0.15R edge needs around 300. This is why the calculator above reports significance alongside expectancy — and why professionals talk about edges per hundred trades, not per week. It's also why journaling every trade matters: the sample is the proof.

The same math runs in reverse. A losing streak of five proves nothing negative about a 0.375R edge — at a 55% win rate, five straight losses happen about once every 54 sequences, which an active day trader hits regularly. Judge the strategy on the sample, not the streak.

From expectancy to projections — carefully

Once expectancy is established, projection is multiplication: expectancy × trades per day × risk per trade. The 0.375R trader risking $200 across three daily trades expects about $225 a day, $4,500 over a 20-session month. The calculator above runs these numbers for your inputs.

Treat projections as a ceiling, not a promise. Real results degrade for predictable reasons: expectancy measured during one market regime (trending, high volatility) fades in another; costs and slippage grow with size; and the trader executing trade 400 is rarely as selective as the one who logged the first 100. Re-measure expectancy on a rolling window — per setup, not blended — and the projection stays honest.

The mistakes that corrupt the measurement

Measuring in dollars instead of R. Dollar P/L mixes edge with position size. One oversized revenge trade can swing a month's dollar total while the per-R record shows exactly what happened.

Blending setups. A 0.5R breakout edge averaged with a −0.1R boredom-trade habit reports as a mediocre 0.2R blend. Tag every trade by setup and compute expectancy per edge — it's usually one or two setups carrying the rest.

Excluding the trades you wish you hadn't taken. If it risked money, it's in the sample. The plan-violation trades are part of your real expectancy until they stop happening.

Frequently asked questions

What is trading expectancy?

The average amount you make or lose per trade in R: (win rate × avg win R) − (loss rate × avg loss R). A 55% win rate with 1.5R winners and 1R losers gives +0.375R per trade.

What is a good expectancy for a day trader?

After costs, a sustained 0.1–0.3R per trade is solid intraday; 0.3R+ is excellent. Numbers far above that usually signal a small sample or untracked costs.

Can a high win rate still lose money?

Yes — 70% winners at 0.3R against 1R losers is −0.09R per trade. Win rate and payoff only mean something together.

How many trades to confirm an edge?

Roughly (2σ ÷ expectancy)². With typical intraday variance, a 0.3R edge needs ~75 trades; a 0.15R edge needs ~300.

Expectancy vs profit factor?

Expectancy is average R per trade; profit factor is gross profit ÷ gross loss. Same edge, different lens — expectancy forecasts better because it scales with trade count and risk size.