Trading Expectancy Formula: How to Tell if a Strategy Is Worth Trading

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Last updated: 16 October 2026 · By Spencer Li, CFTe

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Expectancy is the average amount a strategy makes or loses per trade. The formula is: expectancy = (win rate × average win) − (loss rate × average loss). Measure the wins and losses in R, where R is the amount you risk on each trade, and the answer tells you how many R the strategy earns or gives back on an average trade.

A hypothetical example: a strategy wins 40% of the time, its average win is 2.5R and its average loss is 1R. Its expectancy is 0.4 × 2.5 − 0.6 × 1, which comes to +0.4R per trade. Positive expectancy means the strategy has an edge. Zero or negative means it does not, however good the win rate looks.

Expectancy is the number that decides if a strategy is worth trading at all. It is also the number most traders never calculate, because it needs a written record of every trade.

What does expectancy tell you that win rate cannot?

Win rate tells you how often you are right. Expectancy tells you if being right pays. The 2 can point in opposite directions.

In September 2026 a trader on r/Daytrading posted a short warning to newer traders: “you can lose money winning 90% of them”. He finished with the line that sums up this whole post: “Win rate feels good, but expectancy is what actually matters.”

Here is the hypothetical arithmetic behind his point. A strategy wins 90% of its trades, but each win makes only 0.1R, while each loss costs 1R. Its expectancy is 0.9 × 0.1 − 0.1 × 1, which is −0.01R per trade. It wins 9 trades in 10 and still loses money slowly.

This is why I call it the 3-number test. Before you trust any strategy, yours or anyone else’s, ask for 3 numbers: the win rate, the average win and the average loss. Those 3 give you expectancy. A win rate on its own gives you nothing you can use. How the first 2 trade off against each other is the subject of win rate versus reward-to-risk.

Why measure expectancy in R instead of money?

Because R makes every trade comparable. A loss of 1R is a loss of exactly what you planned to risk, whether your account is small or large and whatever the price of the stock. A win of 3R is 3 times what you risked.

To turn any closed trade into an R-multiple, divide the result by the amount you risked when you entered. Risk 1% of the account and make 2.5%, and that trade is +2.5R. Risk 1% and get stopped out for 1%, and it is −1R. Let a loser run past the stop to 1.5%, and it is −1.5R, which your journal should show honestly.

The casino idea from trading versus gambling is the same thing in different clothes. A casino’s house edge is its expectancy per bet. It is small, it is positive, and the casino lets the number of bets do the rest.

How do you calculate expectancy from your own trades?

Take your last batch of closed trades, write each one as an R-multiple, and average them. The average R-multiple is your expectancy. Here are 10 hypothetical trades:

The 10 results add up to +2R, so the average is +0.2R per trade. The formula gives the same answer. The win rate is 40%, the average win is 1.875R and the average loss is about 0.92R, and 0.4 × 1.875 − 0.6 × 0.92 comes to +0.2R.

Then take off your costs. Commissions, spreads and slippage can be written in R too. If they come to 0.05R a trade, a strategy at +0.2R is really earning +0.15R, and a thin edge can disappear entirely.

If you do not have the 10 rows yet, start there. Keeping a trading journal shows a simple way to record them.

If you want a daily routine that keeps every trade on the record, the free 15-Minute Swing Trader’s Checklist is at the end of this post.

[INFOGRAPHIC: the 3-number test as a card: win rate, average win and average loss feeding into one expectancy figure, with the 90% win rate strategy shown failing it and the 40% strategy passing]

How many trades does it take to trust the number?

More than most people expect. Ten trades tell you very little, even about a strategy with a real edge.

Take the +0.4R strategy from the top of this post and run it many times in a simulation. Here is how often the trader would see a flat or losing average, purely from the luck of the draw:

Hypothetical, each trade independent, 20,000 simulated runs per row.

Read the second row again. After 30 trades, a genuinely good strategy still looks flat or negative about 1 time in 10. That is why we ask for 100 to 200 trades before judging a system, and why the law of large numbers gets a post of its own.

Can a positive expectancy stop working?

Yes, and this is the fair objection to everything above. Expectancy is measured on trades that already happened. A trader on r/algotrading posted in January 2026 about tracking “Strategy Decay”, the way an edge can fade as markets change.

He is right to worry about it, because a number measured on last year’s trades describes last year’s market, and the conditions that produced the edge can shift without any warning at all. Personally, I re-check expectancy on a rolling batch of recent trades as well as the full history. If the recent number drifts well below the long-run one, that is a reason to look harder at the method before the account forces the question.

2 more things expectancy does not tell you. It says nothing about how deep the losing streaks get along the way, which is what risk of ruin is for. And it is per trade, so frequency matters. A strategy at +0.2R that trades 100 times a year earns 20R, while one at +0.5R that trades 20 times earns 10R.

The full map of these ideas sits in the practical guide to money and risk management.

No casino has ever needed to know how the next spin will land. It only needs to know its number, and to keep the bets small enough that the number gets time to show up.

FAQ

What is the formula for expectancy in trading?

Expectancy = (win rate × average win) − (loss rate × average loss). With wins and losses in R, the answer is the average R made or lost per trade.

What is a good expectancy for a trading strategy?

Any figure that stays positive after costs over a large sample. How big it needs to be depends on how often the strategy trades.

Can a strategy with a high win rate have negative expectancy?

Yes. A strategy that wins 90% of the time at 0.1R and loses 1R on the rest has an expectancy of −0.01R per trade.

How many trades do I need to calculate expectancy?

At least 100 before trusting it, and ideally 200. Below 30 trades, luck can hide a good strategy or flatter a bad one.

Is expectancy the same as expected return?

They come from the same maths, the probability-weighted average outcome. Expected return is the investing term for an asset’s average return, while trading expectancy is measured per trade, in R.

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About the author. Spencer Li is the founder of Synapse Trading and a Certified Financial Technician (CFTe). His trade log is public: every trade since April 2024, dated, losses left in.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

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Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.