The video-native data platform for sports AI teams
From player tracking and pose estimation to event tagging and broadcast analytics, Encord gives sports AI teams the annotation speed, data curation, and model evaluation infrastructure to ship faster.
Why sports AI teams are switching to Encord.
Video-Native Annotation at Frame Accuracy
Annotate full match video, player tracking data, and pose sequences in one interface. No re-encoding, no frame extraction, no lag. Sub-pixel keypoint precision for biomechanics and tracking tasks.
Video-Native Annotation at Frame Accuracy
Annotate full match video, player tracking data, and pose sequences in one interface. No re-encoding, no frame extraction, no lag. Sub-pixel keypoint precision for biomechanics and tracking tasks.
Intelligent data curation before you label
Stop labeling random samples. Find underrepresented scenarios, like night games or edge-case formations, before annotation begins. Filter by embedding similarity, metadata, or custom model outputs.
Multi-Camera view of synchronised footage
Handle multi-view synchronised footage, projection matrices, and homography natively. No custom scripts required. Built for broadcast, tracking, and pitch-level reconstruction workflows.
Replace internal tooling without the disruption
Built-in tooling for tracking pipelines is expensive to maintain and slow to extend. Encord provides a production-ready, API-first platform your models team can wire into existing S3 and MLOps infrastructure in days.
Replace internal tooling without the disruption
Built-in tooling for tracking pipelines is expensive to maintain and slow to extend. Encord provides a production-ready, API-first platform your models team can wire into existing S3 and MLOps infrastructure in days.
"Nothing beats looking at the data, and Encord just makes that a lot easier."
Additional resources for sports AI teams
Frequently asked questions
The switching cost is almost always lower than it appears, especially when you account for the ongoing engineering time to maintain and extend an internal tool. Most sports AI teams using home-grown systems face the same issues: slow feature development, no pre-labeling support, and fragile pipelines that break when ontologies change. Encord integrates with your existing S3 buckets and ML infrastructure, so migration is typically completed in days, not months. We also offer a structured onboarding process and can help with data migration.
Encord streams video natively from your cloud storage (S3, GCS, Azure). Annotators never need to download footage locally. The editor handles 4K, high frame rate, and multi-camera footage without re-encoding or resolution loss. Frame-accurate navigation and object tracking work at scale even on lower-spec hardware.
Yes, your models provide the initial pass, but Encord gives your human reviewers a structured interface to inspect, correct, and approve before anything enters your training pipeline. Without a proper review layer, model errors compound silently. Encord's workflow engine routes tasks automatically, enforces QA standards, and gives you full traceability on every label: who annotated it, when, under what instructions, and what quality score it received.
Yes. Encord natively supports multi-camera synchronised projects, projection matrix handling, homography, and 3D bounding box annotation with world coordinates. Teams tracking player positions across pitch-level cameras, or building broadcast analytics with multiple angles, can work entirely within Encord without custom scripts for camera calibration or frame synchronisation.
Encord Index lets you compute and visualise embeddings across your dataset to find clusters, outliers, and coverage gaps before or after annotation. If your player detection model is failing on low-light sequences or unusual formations, you can search your raw data for those exact scenarios, curate targeted subsets, and prioritise labeling effort there. This closes the loop between model performance signals and data improvement, which is the key to faster training iteration.
Encord supports multi-region data residency and can be configured so annotators connect to data stored closest to their geography, reducing latency significantly. Workflow management, task assignment, and QA are all handled centrally, so your operations team has full visibility regardless of where annotators are located. We also offer enterprise deployment options including virtual private cloud for teams with strict data governance requirements.