Intelligent Coaching Tablet for Sports Injury Prediction in Basketball

A US startup was developing an innovative product — an intelligent tablet for basketball coaches that analyzes the risk of player injuries in real-time based on behavioral and game data. The target audience is professional and semi-professional basketball teams, academies, and sports doctors.

The client came with an idea and a willingness to invest in an MVP. There was no architecture, layouts, or business logic. We took on the full development cycle: from requirements gathering to product launch into production.

Problem / Task

We faced a complex set of tasks:

• Designing and implementing the architecture from scratch.
• Interactive UX/UI design with a focus on speed of perception and tablet usability.
• Support for live video analytics with elements of Computer Vision (CV).
• Displaying a 3D model of the match with the ability to control visualization.
• Building a backend service with predictive analytics and an API.
• Deploying cloud infrastructure and DevOps.
• Ensuring the stable operation of the MVP in a live match environment.

Solution

Our team provided completely custom development:

• Backend: prediction service in Python with a REST API, built on FastAPI and PostgreSQL.
• Frontend: cross-platform SPA in React with an adaptive tablet version.
• CV Module: basic player tracking model for video stream, integration with live data.
• 3D Visualization: WebGL engine for displaying the court, player movement, and events.
• DevOps: cloud infrastructure in AWS (EC2, S3, RDS, CloudWatch), CI/CD pipeline.
• Integration: WebSocket for data streaming, REST API for analytics and management.

The MVP was adapted for live mode and worked locally on tablets with the possibility of partial processing in the cloud.

Process

Development took 5 months and included:

• Requirements gathering and architecture design.
• Creating interactive UX/UI prototypes.
• Parallel backend and frontend development.
• Training and integration of the CV module.
• Deployment of the cloud environment and CI/CD automation.
• Integration and load testing.
• Preparation for production and release of the first version to a limited pool of users.

Agile methodologies, weekly sprints, and continuous validation of solutions with the client were used.

Result

• The MVP was released on time and passed successful pilot testing in a basketball academy.
• Player tracking in live video works with 92% stability.
• Analysis of injury risk based on positions, speed, and sudden movements — in real-time.
• The 3D model of the court and movements provides a clear view for the coach and allows for “rewinding” events.
• The cloud architecture scales for future teams and competitions.
• Application response time — less than 400 ms in live mode.
• The first version supports up to 10 players simultaneously.
• The client attracted the next round of investment and continues to actively develop the product, including expanding CV modules and integrating with wearables.

Features / Challenges

• Development was done from scratch, without initial artifacts — we assembled a team of architects, designers, and engineers.
• The CV module required working with unstable streams from different cameras — we applied a hybrid detector with compensation and tracking.
• Visualizing players in 3D required synchronizing data from the live stream with WebGL.
• It was necessary to ensure offline operation — a critically important part of the analysis works locally.

Interesting Facts

• Initial tests showed the predictions matched the facts — a player to whom the system assigned a high risk was substituted 5 minutes before a potential injury.
• The 3D court became not only an analytical tool but also an excellent means for presentations and training sessions.
• One of the analysts uses the system as a “second screen” to assess the behavior of players off the ball.

Feedback

“This is not just an MVP, but a working product that helps on the court today. The team was deeply engaged in the task, and we were amazed by the speed at which the first prototype was assembled. The visualization and ease of use for coaches were particularly impressive.”

Mykhailo Smorodin

CEO at Paradigma.ST, Computer Vision and AI in Sports Tech

Motivated and entrepreneurial software engineer with a passion for artificial intelligence, computer vision, and sports. Skilled in developing innovative solutions and driving projects from concept to completion. Eager to leverage my technical expertise and business acumen to create impactful advancements in technology.