How Thinksys Helped Track160 Achieve 90% More Reliable Match Recording?

Sports analytics companies depend on reliable, real-time match data to deliver precise insights to teams and analysts. When systems fail to capture, tag, or deliver this data, the result is missed insights, unhappy clients, and lost business. Unreliable recordings, slow event validation, and inefficient workflows directly impact their business.

Track160 faced similar problems. Unreliable match recording and inefficient event tagging slowed their ability to deliver accurate analytics, affecting both operations and client relationships.

This case study shows how we overhauled Track160’s match analysis workflow, improved reliability, and built scalable, efficient tagging systems, which will help them prepare for the next wave of innovation in sports analytics.

Meet Track160

Track160 delivers advanced analytics for football matches, giving clubs, coaches, and analysts the real-time data they need to make decisions. Their platform brings together live video, player tracking, and event tagging for actionable insights.

As Track160 grew, new technical and operational hurdles appeared:

• Unreliable match recording: Camera connectivity drops during setup meant missing out on key match footage.
• Large file upload failures: Uploading high-res recordings to S3 often failed, stalling the analysis pipeline.
• Tagging delay due to long match duration: Reviewers had to sit through the entire 90-minute game to verify events, slowing down their reviewing speed.
• Mobile stats lag: Player stats tooltips lag because of mismatched resolution coordinates, hurting the mobile experience.
• Manual tagging issues: Tagging events and players took too long, with little automation or workflow support.

Without a scalable fix, Track160 risked falling behind on delivering timely, accurate match data to clients.

Solutions

To fix Track160’s pain points, we mapped out a set of practical, high-impact changes:

• Auto-retry for camera connections: Built-in automatic reconnection for IP cameras, so recording wouldn’t stop if the network dropped for a moment.
• Smarter file handling and chunked uploads: Reduced recording file sizes and switched to chunked uploads, making large file transfers to S3 much more reliable.
• Web-based recording platform: Started building an online recorder, using message queues (like RabbitMQ) to connect the web UI and the recording app.
• Automated event validation tools: Created tools to pull in pre-processed data, letting reviewers check events quickly and cut down on manual QA work.
• Mobile app performance upgrades: Improved coordinate conversion logic and explored cross-platform frameworks (like Flutter) to make real-time stats faster and smoother on mobile.
• Flexible tagging workflows: Designed a tagging tool that supports both manual and automated event capture, with structured outputs for analytics and reporting.

These solutions made Track160’s match analysis workflow more reliable, efficient, and ready to scale for the future.

Results

Here’s what changed for Track160 after these improvements:

1. Recording Reliability Jumped 90%: Auto-retry for camera connections and smarter file handling meant every critical match was captured, ensuring no more lost footage.
2. Large File Uploads Became Routine: Chunked uploads and better error handling made even the biggest files upload smoothly, so the analysis pipeline kept moving.
3. Tagging Got Faster: Automated event validation and a streamlined tagging process let reviewers handle more matches, more accurately, in less time.
4. Tagging Workflows Now Adapt to Any Need: Tools now support both manual and automated event capture, with structured outputs ready for analytics and reporting across systems.
5. Mobile Stats Are Truly Real-Time: The mobile app is faster and more responsive, with improved coordinate logic for a better experience on the go.
6. Ready for What’s Next: Modular, web-based systems (like remote-controlled tagging and recording) set Track160 up for new features and future growth.

The next sections break down exactly how these results were achieved, step by step, with the technical details behind each improvement.

Steps Taken

1. Step 1: Made Match Recording Strong
2. Step 2: Large File Uploads without Any Stress.
3. Step 3: Tagging Is Really Fast
4. Step 4: Tagging Workflows That Can be Scaled
5. Step 5: Real-Time and Accurate Mobile Stats 
6. Step 6: Built for the Future

Conclusion

Track160’s journey is a proof that targeted technical changes and modular tools can reshape sports analytics. By focusing on reliability, efficiency, and scalability, Track160 now delivers accurate, real-time match data that coaches, analysts, and players can use when they need it.

If you’re facing challenges with data capture, tagging, or real-time analytics, ThinkSys experts are here to help you build a foundation for solutions that resolve your issues and are future-ready.