Model-assisted labeling behind an AI volleyball coach, run by a two-person team.
Read the story- to prep a dataset, down from weeks
- Days
- model retraining loop
- Overnight
CVAT for Sports & Media AI
CVAT turns match footage, training clips, and video ads into validated training data for player tracking, pose analysis, and highlight detection, trusted by teams like Younalize.
Use cases
Turn Every Frame of Play Into Ground Truth
Player and ball tracking
Track every player and the ball across frames for tactics and stats.
Pose and technique analysis
Mark body keypoints to measure joint angles and movement phases.
Broadcast and highlight detection
Tag shots, fouls, and key moments for automated clips.
Ad and creative analysis
Track products and attention-critical areas across video ads.
Fitness and training apps
Label form, reps, and equipment in smartphone workout clips.
How it Works
Integrate Seamlessly
Start labeling without changing how you work
Connect your match and training footage, existing labels, and review stages as they are. Nothing to re-plumb.
Book a demoProjects/match-tracking-2026
Search sourcesAdd source
SourceStatus
1s3://match-footage/season-26Syncing…
2gs://training-clips/academySyncing…
3azure://broadcast-archive/2026Syncing…
4labels_v2 · COCO Keypoints 1.0Syncing…
5Annotation → Validation → AcceptanceSyncing…
6webhook update:job → trainingSyncing…
7labeling_guidelines_v2.pdfSyncing…
Accelerate Validation
Clear labeling backlogs faster
AI pre-labels every frame. Your analysts or our experts fix what it misses.
Book a demoJobs/Match 31 · Frame 4820
referee #1
player #2
player #3
player #4
ball #5
Ship with Confidence
Catch label errors before they reach training
Every job is scored against ground truth, so only clean data reaches training.
Book a demoTasks/Quality control
Mean annotation quality
98.4%
Target 95%
Honeypots
CVAT is how ML teams ship sports AI.
