> ## Documentation Index
> Fetch the complete documentation index at: https://help.turtlemetrics.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Tag Analysis

> Analyze how your tagged behaviors and patterns affect trading performance.

Tag analysis turns your trade observations into performance data. Every tag you assign to a trade becomes a filter you can measure against — showing you exactly which behaviors, conditions, and patterns are helping or hurting your bottom line.

## 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:

<AccordionGroup>
  <Accordion title="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.
  </Accordion>

  <Accordion title="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.
  </Accordion>

  <Accordion title="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.
  </Accordion>

  <Accordion title="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.
  </Accordion>
</AccordionGroup>

## Combining tags with setups

Tag analysis becomes even more powerful when you cross-reference it with [setup analysis](/features/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.

<Info>
  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.
</Info>

## Tips for getting the most out of tag analysis

1. **Be consistent** — Tag every trade, not just the interesting ones. Gaps in your data skew the results.
2. **Wait for sample size** — Tags with fewer than 20–30 trades aren't statistically reliable yet. Be patient.
3. **Review monthly** — Check your tag performance at least once a month to catch patterns early.
4. **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.

## Related

<CardGroup cols={2}>
  <Card icon="tags" href="/features/tags-and-categories" title="Tags & Categories">
    Set up and manage your tagging system.
  </Card>

  <Card icon="lightbulb" href="/concepts/tags-vs-notes" title="Why Tags Beat Notes">
    The philosophy behind structured tagging.
  </Card>
</CardGroup>