Jersey number recognition: Datasets & Models
Automatically read and identify player jersey numbers from game footage and photos using OCR. Turns raw video frames into structured player-tracking data without manual tagging.
Jersey number recognition
This computer vision workflow performs jersey number detection on images and video frames from sporting events, locating each player and reading the digits on their jersey using OCR. It outputs structured data that ties each recognized number to a specific player, taking game footage or still photos as input.
Try it out
Powered by general detection model
Run on custom image
Drop an image here or click to upload
Why automate jersey number recognition
In sports analytics, manually reviewing footage to log which player did what is slow, tedious, and error-prone, especially across long matches or full seasons of film. Automating jersey number recognition lets teams and media companies tag players frame-by-frame at scale, enabling player tracking, highlight generation, and performance stats without an analyst pausing and scrubbing video by hand. Because numbers appear at varying angles, distances, and under motion blur, a dedicated OCR model handles the variability far more reliably than rule-based cropping or human annotation alone.
Key benefits
Automated jersey number detection dramatically cuts the labor of tagging players and produces consistent, timestamped data that feeds directly into analytics pipelines. It runs on the broadcast, arena, and training-camera feeds teams already have, and scales from a single game clip to entire season archives. The result is faster turnaround on player-level insights and clean structured data for downstream tracking and stats systems.
How to use it
- Upload an image: Drop any photo into the widget above to try jersey number recognition for free, right on this page.
- Preview instant results: The model detects jersey number, player, jersey, referee, sports ball within seconds and returns an annotated image with structured predictions, so you can immediately see how well it works. Adjust the detection classes and re-run until the results fit your scenario.
- Like what you see?: With a free Roboflow account, you can deploy this workflow with the Serverless Cloud API, customize it in your workspace, or train OCR / document model on your own images for production accuracy.
- Get started for free: No code or training data required to begin: upload, review the results, and make it part of your stack in a single click.
Recommended model for jersey number recognition
When you're ready to build a production model for jersey number recognition, we recommend training OCR / document model. Unlike the ready-to-use model in the demo above, you fine-tune it on your own labeled images for higher accuracy, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Jersey Number Recognition project to Roboflow Agent.