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

# Normative Ranges

> How to Interpret Uplift Normative Ranges

Uplift provides normative ranges in two places: **exact percentile estimates** in  reports, and **reference tables** in the Movement Library.
Both allow for comparison of an athlete's result against their peer population data.

## Specific Percentiles in Uplift Reports

Signals reports show an exact percentile (e.g. 77th, 33rd) for each continuous metric, telling you where the athlete ranks within their population group.

* **77th percentile** → the athlete's value is higher than 77% of similar athletes.
* **33rd percentile** → the athlete's value is higher than only 33% — roughly the lower third.

Use these bands as a quick guide:

| Percentile     | What it means                    |
| -------------- | -------------------------------- |
| 90th +         | Elite — top 10%                  |
| 75th – 89th    | Above average                    |
| 25th – 74th    | Average                          |
| 11th – 24th    | Below average                    |
| 10th and below | Low — likely a training priority |

**Direction matters.** A high percentile isn't always good:

* *Higher is better* metrics (e.g. peak velocity) — higher percentile = better.
* *Lower is better* metrics (e.g. flag rates) — lower percentile = better.
* *Middle is optimal* metrics — 25th–75th is the target; extremes in either direction are suboptimal.

Percentiles are most useful when tracked over time. A shift from the 40th to the 60th percentile across a training block signals real progress, even if both sit in the "average" band.

## Normative Range Tables in the Movement Library

Metric pages show a broader reference table with five percentile breakpoints (10th, 25th, 50th, 75th, 90th) across up to five competition levels.

| Population             | Description                                   |
| ---------------------- | --------------------------------------------- |
| **Youth**              | Middle school or younger (typically under 14) |
| **High School**        | Ages 14–18                                    |
| **College**            | Collegiate athletes                           |
| **Professional**       | Professional or elite athletes                |
| **Broad (All Levels)** | All athletes combined                         |

The **Optimal Range** column highlights the target window based on the metric's direction — 75th–90th for higher-is-better, 10th–25th for lower-is-better, and 25th–75th for middle-is-optimal.

Use these tables to understand what a good value looks like for a given population, and to give context to the exact percentile shown in a Signals report.

### Data source

Normative data is filtered to remove outliers and poor-quality tracking sessions before percentiles are computed. The *baseball-hitting* and *baseball-pitching* analyses reference the **2026 Q1 dataset**, covering all sessions from the 2025 calendar year.