The Top 5 Data Labeling Platforms Powering Sports AI in 2025

From tracking every movement on the court to breaking down biomechanics frame by frame, Sports AI is rewriting how athletes train and perform. None of that is possible without accurate, well-labeled datasets. 

The importance of high-quality data is crucial for the performance of sports AI models in production because a number of edge cases naturally appear, whether that is sports played in different lighting and weather conditions or tracking and segmenting objects where occlusions are likely to occur. 

Sports data comes with quirks:

• Multiple camera angles that need syncing
• High-speed action where players and balls move unpredictably
• Pose and skeleton labeling for biomechanics and injury prevention
• Privacy concerns when working with biometric or medical data

Therefore, choosing the right data labeling platform ensures that the complexity of sports AI data and model performance can be tackled. Let’s dive into the top platforms driving the future of sports analytics! 

1. Encord – The All-in-One Platform for Sports AI

If you’re looking for a single platform that handles everything from labeling to dataset management to model evaluation, Encord is the clear leader. It was designed with complex, multimodal workflows in mind which is exactly what sports AI demands.

Highlights:

• Annotate video, 3D, images and more. The platform is truly multimodal
• Pose estimation tools for skeletons, keypoints, and trajectories
• Smart automation that cuts repetitive labeling time
• Compliance-ready for sensitive medical or performance data
• Built for enterprise-scale projects like professional sports leagues
• Has embeddings plots and similarity search for surfacing edge cases efficiently

Best fit: Pro teams, sports tech companies, and labs that want an end-to-end solution.

2. Segments.ai – Multi-Camera & 3D Synchronization

Sports rarely happen in one frame. Segments.ai makes it easy to label across multiple angles and 3D inputs, which is essential for sports like soccer, basketball, and tennis.

Highlights:

• Synchronize and annotate video + LiDAR/3D
• Track players and balls across frames
• Semi-automated interpolation to speed up workflows
• Collaboration tools to keep datasets versioned and clean

Best fit: Multi-camera sports analytics and broadcast teams.

3. Scale AI – Broadcast-Grade Labeling at Volume

Scale AI is known for sheer capacity. It’s ideal for sports broadcasters, leagues, and media companies that need to label huge datasets for highlights, replays, and player tracking

Highlights:

• High-throughput video annotation for broadcast feeds
• Temporal segmentation and trajectory tracking
• Human-in-the-loop QA to maintain accuracy at scale
• Integrations with production AI pipelines

Best fit: Large-scale broadcast or fan engagement applications.

4. Kili Technology – Lightweight but Effective

Kili gives smaller teams the tools they need without overwhelming complexity. It supports pose, bounding boxes, and segmentation, making it handy for early-stage projects.

Highlights:

• Easy-to-use video annotation tools
• Automation powered by models like SAM
• Affordable and flexible

Best fit: Sports AI startups and research groups testing new ideas.

5. CVAT – The Researcher’s Favorite

As an open-source tool, CVAT has long been popular in academic circles. It’s especially useful if you’re building custom models or experimenting with new annotation types.

Highlights:

• Keypoints, bounding boxes, and trajectory tools
• Extendable with custom plugins
• Large community for support

Best fit: Universities and sports research labs.

Which Platform Fits Your Sports AI Project?

Why Encord is #1 for Sports AI

The demands of Sports AI, like fast-moving athletes, multi-angle video, and sensitive biometric data, call for more than basic annotation. You need a platform that can handle video, 3D, automation, QA, and compliance in one place.

That’s why Encord is the clear choice. It doesn’t just label. Rather, it manages the entire data pipeline, from raw footage to model-ready datasets. For professional teams, sports scientists, and broadcasters, Encord is the most complete data platform available in 2025.

👉 Ready to level up your Sports AI workflows? Explore Encord’s Data Labeling Platform.