Rosters: Use AI to Structure Names, Jerseys, and Positions

Rosters are one of the most reused inputs in coverage — and one of the easiest places for small errors to creep in over time. uReport now supports AI-assisted roster discovery to help teams structure roster data for reuse across stories.

What roster structuring includes

When roster data is available, uReport can identify and normalize common fields such as:

• Name
• Jersey number
• Position
• Other attributes when they exist in the source

How teams use structured rosters

• Spotlights: Create consistent player/participant profiles without retyping the basics.
• Recaps: Reference multiple athletes/participants with fewer mistakes and less copy/paste.
• Season-long consistency: Keep naming and identifiers stable across many stories.

Why this matters

• Consistency: fewer spelling errors and mismatched identifiers
• Speed: less repetitive data entry
• Reuse: roster info becomes a stable foundation for repeatable formats

Support note

AI extraction depends on the source. If a roster is incomplete or formatted unusually, results may be partial on the first pass. Providing a cleaner roster source typically improves extraction quickly.