How to Analyze Your Trading Performance by Strategy and Setup
Reviewed by Leon Moyer - Published October 9, 2026 - Last reviewed October 9, 2026
In this lesson
Split a journal by strategy and then by one condition, measure each group, and decide which differences are worth testing.
Analyzing your trading performance means splitting your closed trades into groups that share something, such as a strategy, a setup or a condition at entry, and measuring each group's result after fees. The totals for a whole journal tell you whether you made money; the groups tell you where it came from.
This lesson puts the two measures from earlier in the module, trading expectancy and profit factor, to work on the tags from How to Find Your Trading Edge.
Why look at results by strategy at all?
Because a journal is usually a mix. A trader might buy calls, sell put spreads and write covered calls in the same month. If one of those makes money and another loses it, the total can look acceptable while one strategy quietly drains the account. Splitting by strategy is the first cut every journal deserves.
Worked example
Journal A split by strategy
Journal A from Trading Expectancy has 40 trades: 24 winners averaging $100, 16 losers averaging $120, an expectancy of $12 per trade. Its strategy tags split it in two:
The spreads won 70% of the time and the long calls only 50%, yet the long calls earned five times as much per trade. The spreads' average loss of $220 nearly cancels their more frequent wins. Notice that the two groups add back up to the whole journal: $80 + $400 = $480.
Illustrative and hypothetical. The ticker and prices are invented for teaching, and the figures exclude commissions, fees, margin interest and taxes, which reduce real results. Past or hypothetical outcomes do not indicate future results.
Journal A split by strategy
Expectancy per trade
Net result, 20 trades each
The table does not say "stop selling spreads". It says the spreads, as traded, have been close to break-even, and that their losses deserve a closer look.
How do you split results by setup and conditions?
Once a strategy stands out, split that strategy by one more field to look for an explanation. Good candidates are the fields you recorded at entry: setup tag, days to expiration, implied volatility, and whether an event such as earnings fell before expiration.
Worked example
The 20 put spreads split by earnings
The spreads' "conditions" field records whether an earnings report fell before expiration:
- Held through earnings (5 trades): 2 winners ($200) and 3 losers ($660). Net -$460, or -$92 per trade.
- No earnings before expiration (15 trades): 12 winners ($1,200) and 3 losers ($660). Net +$540, or $36 per trade, with a profit factor of about 1.82.
Check: -$460 + $540 = $80, the spreads' total. Half of the spreads' losing trades came from the five that were held through earnings.
Illustrative and hypothetical. The ticker and prices are invented for teaching, and the figures exclude commissions, fees, margin interest and taxes, which reduce real results. Past or hypothetical outcomes do not indicate future results.
The 20 put spreads split by earnings
Held through earnings (5 trades)
No earnings before expiration (15 trades)
This is a plausible pattern. An earnings report can move a stock sharply overnight, which is exactly the kind of move that sends a short put spread to its maximum loss. But it rests on five trades. That is a lead to test, not a rule, and How Many Trades Do You Need? shows why.
What are the rules for splitting a journal well?
- One field at a time. Split by strategy, then split one strategy by one condition. Splitting by three fields at once produces groups of two or three trades that mean nothing.
- Write the count next to every number. A $36 expectancy over 15 trades and a $36 expectancy over 150 trades are not the same finding.
- Prefer R when sizes differ. If you traded one strategy at twice the size of another, compare expectancy in R, not in dollars.
- Make the groups add up. Every trade belongs to exactly one group in a split, and the groups' totals should equal the whole. If they do not, some trades are untagged or double-counted.
- Look at plan-following separately. If most of a strategy's losses came from trades where you broke the plan, the problem is discipline, not the strategy. The Course 1 journal lesson shows that sort.
- Have a reason. A split you can explain in market terms, such as earnings risk for short premium, is more likely to hold up than one you cannot, such as "trades entered on Tuesdays".
What should you do with what you find?
A difference between groups is a hypothesis, not a conclusion. Turn it into a written rule you could test, such as "close or skip short put spreads with an earnings report before expiration", and then check it on trades you take after writing it down. How Many Trades Do You Need? covers how many trades that takes and how to avoid fooling yourself along the way.
Check your understanding
In the strategy split, which group won more often, and which made more per trade?
Show answer
The bull put spreads won more often (70% versus 50%), but the long calls made more per trade ($20 versus $4), because the spreads' average loss was much larger.
Why split one strategy by one condition, instead of the whole journal by several fields at once?
Show answer
Because every extra field cuts the groups smaller. Several fields at once leave groups of a few trades each, too small to tell a real pattern from chance.
The five spreads held through earnings lost $460. Is that enough to make a permanent rule?
Show answer
No. Five trades is far too few to be confident. It is a reasonable hypothesis to write down and test on future trades.
Key takeaways
- Split closed trades by one field at a time and measure each group's count, net result, expectancy and profit factor after fees.
- Start with strategy, then split a standout strategy by one condition recorded at entry.
- The groups in a split should add back up to the whole journal.
- A difference between groups is a hypothesis to test on new trades, especially when a group is small.
Common questions
How do you analyze trading performance?
Group closed trades by one field at a time, such as strategy, setup or days to expiration, and calculate each group's number of trades, net result, expectancy and profit factor after fees. Then compare the groups, paying attention to how many trades each one holds.
What metrics should I use to evaluate my trading?
Start with the number of trades, net result after fees, expectancy per trade (in dollars and in R) and profit factor. Win rate is useful only alongside average win and average loss, because on its own it hides the size of the losses.
How do I know which trading strategy works best for me?
Compare expectancy per trade for each strategy over a meaningful number of trades, preferably in R so position sizes do not distort the comparison. Then confirm the leader on new trades before shifting more capital to it.
Should I stop trading a strategy that has negative results?
Not on a small sample alone. First check how many trades the result rests on, whether the losses came from breaking the plan, and whether one condition explains them. A strategy that stays negative over many trades taken as planned is a strong candidate to drop or change.