Custom Basketball Video Analysis Software. No Sensors Required.

We build custom basketball video analysis software for tech startups, smart courts, clubs, and academies. Use standard cameras to automate shot tracking (make/miss), generate shot charts, and analyze spacing and possessions in near real time.

Why Hardware Limits the Game

Sensor-based systems are costly, hard to maintain, and difficult to scale across multiple courts. Video-first AI provides a simpler path: capture games with standard cameras and extract performance insights without wearables or specialized tracking kits.

The “Smart Court” Cos

The “Smart Court” Cost

Hardware-heavy setups raise upfront and ongoing costs across venues and programs. Video-first systems reduce friction while keeping insights consistent.

Limited to Data Checks

Manual Data Entry

Staff time gets consumed by tagging plays, tracking shots, and compiling reports. AI automation gives teams insights faster with less operational overhead.

Biomechanical Blindness

Biomechanical Blindness

Sensors don’t explain what happened on the court. Video analytics connects shot outcomes to context like spacing, contest pressure, and positioning.

Scaling Across Venues

Scaling Across Venues

Sensor-based setups lock you into per-court hardware costs. Video-first systems scale across facilities using existing camera infrastructure, no retrofitting required.

Solutions for the Basketball Ecosystem

From training and development to broadcast-style insights, we build custom systems that fit your level of play and your product roadmap.

Group 5252

Automated Shot Tracking (Make/Miss)

Automate shot detection and outcomes from video to generate accurate shot charts and trend reports. Ideal for training facilities, teams, and smart court operators.

Mobile Shooting Coach

Mobile Shooting Coach

Build a consumer or team app experience that provides shot feedback, repetition tracking, progress insights, and personalized coaching workflows.

Tactical Spacing Analysis

Tactical Spacing Analytics

Analyze spacing, movement, and possession structure to support coaching decisions. Build views for offensive sets, defensive positioning, and key moments.

How We Engineer the “Swish”

Basketball is fast, crowded, and visually complex. Our approach is designed for real gameplay: motion blur, partial occlusions, varying lighting, and different camera angles.

Step 1_ Dynamic ROI (Region of Interest)

Step 1: Dynamic ROI (Region of Interest)

We isolate relevant court regions so the system can track shots and player movement efficiently, even with changing camera angles.

Step 2_ Occlusion Handling

Step 2: Occlusion Handling

We maintain tracking through overlaps, screens, and player congestion so you don’t lose events during the most important moments.

Step 3_ The _Net Logic_ Classifier

Step 3: The “Net Look” Classifier

We use visual cues around rim and net dynamics to improve make/miss confidence and reduce false detections.

Step 4_ Court Homography

Step 4: Court Homography

We map video coordinates to a consistent court coordinate system so shot charts, heatmaps, and tactical views remain stable across feeds.

Customer Story

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Custom-Built vs Off-the-Shelf Basketball Analysis Tools

From Raw Footage to Shot Charts and Trends A sports technology team needed reliable make/miss automation without adding sensors to courts. We built a video-first pipeline that converts standard camera feeds into shot events, shot charts, and performance summaries that can be delivered inside their existing product. What we delivered Shot detection + make/miss classification Shot chart generation mapped to court coordinates Exportable analytics and API delivery to their app Deployment options aligned to venue constraints

Ready to Change the Game?

Whether you’re building a shooting app or operating smart courts, we can engineer a custom basketball video analytics system designed for your users, your data, and your deployment requirements across the US and Europe.

Ready to Build Your Motion Intelligence System
FAQ SECTION

Frequently asked questions

AI basketball video analysis uses computer vision and machine learning to automatically understand game or training footage and generate insights like shot outcomes, shot charts, and spacing context without manual tagging.
Yes. We build video-based shot tracking that detects shot attempts and classifies outcomes using rim and net context, timing signals, and court mapping.
No. The system is video-first and works with standard cameras. Sensors can be optional if you want to fuse data, but they’re not required.
It can. Performance depends on camera placement and lighting conditions. We design the solution based on your environment and validate with a pilot.
Yes. We can build the experience end-to-end or integrate the analytics into your existing iOS/Android app.
Both are possible. Single-camera systems can support many workflows. Multi-camera setups can improve coverage and accuracy for advanced analytics, wider court coverage, and multi-angle event validation.
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+1 408 365-4638
contact@folio3.ai

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6701 Koll Center Parkway, #250 Pleasanton, CA 94566