Why win rate alone tells you almost nothing
A trader with a 70 percent win rate sounds like a trader with an edge. It is entirely possible for that same trader to be losing money, if the average loser is three times the size of the average winner. A trader at 40 percent can be solidly profitable if the average winner is more than 1.5 times the average loser. Win rate by itself answers one question: how often you're right. It says nothing about whether being right is worth more than being wrong. That second question needs two more numbers next to it: profit factor and average R Multiple.
Setting up the sheet
- Core columns. Date, Instrument, Direction, Entry, Stop, Exit, P&L. Every formula below reads from these.
-
R Multiple column. For a long trade:
=(Exit-Entry)/(Entry-Stop). For a short trade:=(Entry-Exit)/(Stop-Entry). This expresses every result as a multiple of what you actually risked, so a $50 account and a $50,000 account produce numbers you can compare directly. -
Win rate.
=COUNTIF(P&L_range,">0")/COUNT(P&L_range), formatted as a percentage. -
Profit factor.
=SUMIF(P&L_range,">0")/ABS(SUMIF(P&L_range,"<0")). Above 1 means total gains exceed total losses. Below 1 means the opposite, regardless of how often you're winning. - Average R Multiple. AVERAGE of the R Multiple column. This is the single number that tells you the average size of every trade, win or lose, expressed in units of risk.
- A small dashboard tab. Reference all four numbers, win rate, profit factor, average R Multiple, and expectancy, on one summary sheet so they sit next to each other. None of them is trustworthy read alone.
The formula reference table
Copy these directly into a Google Sheets trading journal. Every formula assumes a column of P&L results and a column of R Multiples already exist.
| Metric | Formula | What it tells you |
|---|---|---|
| Win rate | =COUNTIF(PL,">0")/COUNT(PL) | How often a trade closes positive. Meaningless alone. |
| Profit factor | =SUMIF(PL,">0")/ABS(SUMIF(PL,"<0")) | Gross gains divided by gross losses. Below 1.0 means net losing. |
| Average R Multiple | =AVERAGE(R) | The average size of every trade in units of risk. |
| Average winner (R) | =AVERAGEIF(R,">0") | How big your wins are when you win. |
| Average loser (R) | =AVERAGEIF(R,"<0") | How big your losses are when you lose. |
| Expectancy | =(WinRate*AvgWinR)+((1-WinRate)*AvgLossR) | Expected R per trade over a large sample. Positive means the system is profitable long run. |
A worked example with real numbers
Two traders, both with 40 trades logged over a month. Trader A wins 65 percent of the time. Trader B wins 42 percent of the time. Most people assume Trader A is doing better.
| Trader A | Trader B | |
|---|---|---|
| Win rate | 65% | 42% |
| Average winner | 0.7R | 2.1R |
| Average loser | 1.0R | 0.9R |
| Expectancy | 0.65x0.7 minus 0.35x1.0 = 0.11R | 0.42x2.1 minus 0.58x0.9 = 0.36R |
Trader B is right less than half the time and still generates more than three times the expectancy per trade. The formula table above is what surfaces this. Watching your win rate alone would have led you to conclude Trader A was the better trader, and that conclusion would have been wrong.
A 65% win rate at 0.11R expectancy against a 42% win rate at 0.36R expectancy. Win rate is the least useful number on the sheet.
Reading the three numbers together
A below average win rate is not automatically a problem. It depends entirely on what sits in the profit factor and average R Multiple cells next to it. A strategy with a 45 percent win rate and an average R Multiple of positive 1.8 on winners against negative 1.0 on losers is a strategy worth keeping. The same 45 percent win rate with winners averaging 0.6R and losers averaging 1.0R is not, no matter how it feels day to day to be right less than half the time.
This is also why a single bad week should not trigger a strategy change. Forty trades is a reasonable minimum sample before profit factor and expectancy mean anything. Ten trades of a 45 percent win rate strategy can easily produce seven losers in a row through variance alone, and a trader who abandons or doubles the size of a working system after that stretch has confused a losing streak for a broken edge. This connects to a wider question about how much you should actually be risking per trade during a prop firm evaluation, where the daily loss limit turns a normal losing streak into a challenge ending event if position size is wrong.
What a good win rate actually looks like
There is no single correct win rate. What separates a viable system from a losing one is whether expectancy comes out positive over a real sample size. Trend following systems typically run a 30 to 45 percent win rate with large winners. Mean reversion and scalping systems often run 55 to 70 percent with small, tightly controlled winners and losers. Both can work. Both can also fail with the exact same win rate, depending entirely on the R Multiple sitting next to it.
The spreadsheet will tell you exactly what is working. It will not tell you why you keep taking the trade that doesn't fit the numbers.
Common mistakes when tracking these numbers
The most frequent error is calculating win rate and profit factor from a sample too small to mean anything, usually under 20 trades, and treating the result as settled fact. The second most frequent error is defining R inconsistently, measuring risk from the stop loss on some trades and from a fixed dollar amount on others, which quietly corrupts every average that follows. The third is leaving breakeven trades out of the win rate calculation entirely rather than deciding upfront whether they count as wins, losses, or their own category, since that choice changes the number meaningfully once a strategy produces more than a handful of scratched trades.
A smaller but common mistake is updating the sheet in batches once a week rather than after each session. Memory of exactly why a trade was taken fades within a day or two, and the notes column, which matters as much as the numeric columns for spotting behavioral patterns later, gets thinner and more generic the longer it waits.
What the sheet cannot tell you
These formulas answer a strategy question cleanly. They do not answer a behavior question: why a trader who can see, in black and white, that Setup B has a negative expectancy keeps taking Setup B anyway on days when a loss stings. That gap between what the data says and what you actually do with it is its own problem. We have written about why a year of clean journal data still doesn't change the behavior underneath it, and the short version is that seeing a pattern in a spreadsheet and interrupting it in the moment a trade is open are two different skills.
If you are building this sheet from scratch, it is worth deciding whether a spreadsheet is the right tool for you against Notion, TraderSync, or Edgewonk, since formula transparency is Google Sheets' biggest advantage and its biggest limitation at the same time.
Frequently asked questions
What is a good win rate for a prop firm evaluation?
There is no universal good win rate. Most working strategies sit between 40 and 55 percent. What matters for a prop firm evaluation specifically is consistency under the daily loss limit, not a high win rate. A 45 percent win rate with controlled risk per trade clears most evaluations more reliably than a 65 percent win rate with oversized losers, because the evaluation ends on one bad day, not on a bad month.
How do you calculate profit factor in Google Sheets?
Divide gross gains by the absolute value of gross losses using SUMIF. A profit factor of 1.5 means you made 1.5 dollars for every dollar lost. Below 1.0, you are net unprofitable regardless of win rate.
What is R Multiple and why does it matter more than dollar P&L?
R Multiple expresses a trade's result as a multiple of what you risked, rather than a raw dollar figure. A trade that risked 100 dollars and made 200 is a 2R win regardless of account size. Tracking in R lets you compare a small evaluation account against a large funded account using the same numbers.
Can a low win rate strategy still be profitable?
Yes. A strategy with a 35 to 40 percent win rate can be strongly profitable if the average winner is 2R or larger against an average loser of 1R. This is the standard trend following profile: many small controlled losses, occasional large wins.
How many trades do I need before these numbers mean anything?
Treat anything under 30 to 40 trades as noise. A 45 percent win rate strategy can produce seven losers in a row through variance alone in a small sample. Wait for a real sample before concluding a strategy is broken or before increasing size because of a hot streak.
Why does my trading journal look fine but I still fail my evaluation?
The spreadsheet only measures the strategy. It does not measure whether you actually followed it. A trader can have a negative expectancy setup clearly visible in the data and keep taking it anyway on days a loss stings, which is a behavior pattern the numbers alone will never fix.
Funded prop trader at Apex Trader Funding ($100K) and Alpha Capital Group ($100K). MA Psychology candidate at Chandigarh University, with clinical training under Dr. Nitin Sethi and at Japneet Bakhshi Clinic. Cofounded TradeRoot with Khushi Narwal to work at the source of behavioral trading patterns rather than their symptoms.