Bringing the data to every sideline

2026-07-09 · Source: MIT News - Data · Field: Technology & Digital — Data Science & Analytics, Artificial Intelligence & Machine Learning · Depth: Fundamental Awareness, short

Summary

MIT PhD candidate Henry Wang, set to defend his thesis by the end of 2026, is advancing sports analysis and officiating through data and technology. Working with FIFA Innovation in the MIT Sports Lab, Wang develops systems to enhance referee decision-making speed and accuracy, while also broadening access to performance analytics globally. A key project involved creating a semi-automated system that uses players' skeletal data and ball tracking to identify the last player to touch the ball before it goes out of bounds. This prototype aims to assist goal kick and corner kick calls seamlessly, minimizing game interruptions. Wang's professional experience includes two years with the Boston Red Sox and an upcoming role as a senior data scientist with the Philadelphia 76ers after graduation. His work is driven by a desire to improve the sports experience for everyone.

Key takeaway

For research scientists or AI students developing sports analytics tools, consider how your systems can enhance officiating accuracy without disrupting the fan experience. Focus on integrating technologies like skeletal data and ball tracking to provide seamless, real-time assistance for critical in-game decisions. Your work should aim to democratize access to performance data, ensuring broader utility beyond elite professional teams.

Key insights

Data and technology can significantly enhance sports officiating accuracy and democratize performance analytics access.

Principles

• Technology should assist officials without disrupting fan experience.
• Data can democratize access to sports insights.
• Semi-automated systems can improve referee decision accuracy.

Method

A semi-automated system uses players' skeletal data and ball tracking to identify the last player to touch the ball, assisting out-of-bounds decisions like corner kicks.

In practice

• Implement skeletal data and ball tracking for automated event detection.
• Integrate semi-automated tools to assist referee decisions.
• Explore data analytics for strategic sports play optimization.

Topics

• Sports Analytics
• Officiating Technology
• Skeletal Data Tracking
• Ball Tracking
• Automated Event Detection
• Performance Analytics

Best for: Computer Vision Engineer, AI Scientist, Research Scientist, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT News - Data.