How to access it
Go to Analysis → Tags in the sidebar. You’ll see every tag you’ve used, with performance metrics calculated across all trades that carry that tag.What you’ll see
For each tag, TurtleMetrics shows:| Metric | What it tells you |
|---|---|
| Win Rate | What percentage of trades with this tag were profitable |
| Total P&L | Net impact of trades carrying this tag |
| Profit Factor | Gross profit ÷ gross loss for tagged trades |
| Trade Count | How many trades have this tag |
How to read tag data
Tags work best when you compare them against each other. Some examples of what the data might reveal:Execution quality insights
Execution quality insights
If trades tagged “chased entry” have a 30% win rate while trades tagged “patient entry” sit at 62%, that’s a concrete, measurable reason to stop chasing. You can put an actual dollar amount on the cost of impatience.
Market condition patterns
Market condition patterns
If your “choppy market” tag has a 35% win rate but your “trending” tag shows 58%, you might consider sitting out range-bound days or at least reducing your size.
Emotional trading costs
Emotional trading costs
Tags like “revenge trade” or “FOMO” often reveal surprisingly large P&L drains. Seeing the exact dollar cost of revenge trading is more convincing than any trading psychology book.
What you're doing right
What you're doing right
Don’t just track mistakes. Tags like “held to target” or “followed the plan” let you measure and reinforce your good habits.
Combining tags with setups
Tag analysis becomes even more powerful when you cross-reference it with setup analysis. For example, you might discover that your “Pullback to EMA” setup has a great win rate overall, but trades with that setup plus the “low volume” tag consistently lose. That’s a highly specific, actionable insight.Since trades can have multiple tags, a single trade can appear in multiple tag groups. This is by design — it lets you slice your data in many different ways.
Tips for getting the most out of tag analysis
- Be consistent — Tag every trade, not just the interesting ones. Gaps in your data skew the results.
- Wait for sample size — Tags with fewer than 20–30 trades aren’t statistically reliable yet. Be patient.
- Review monthly — Check your tag performance at least once a month to catch patterns early.
- Act on what you find — The data is only useful if you let it change your behavior. If “revenge trade” has a 20% win rate, stop taking revenge trades.