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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.

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.

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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:
PercentileWhat it means
90th +Elite — top 10%
75th – 89thAbove average
25th – 74thAverage
11th – 24thBelow average
10th and belowLow — 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.

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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.
PopulationDescription
YouthMiddle school or younger (typically under 14)
High SchoolAges 14–18
CollegeCollegiate athletes
ProfessionalProfessional 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.

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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.