Building watchable digital twins of 64 World Cup games
A developer explores the technical process of creating 3D digital twins of World Cup soccer matches using computer vision and player tracking data. The article compares various data providers to determine which offers the highest resolution for high-fidelity sports visualization.
Why it matters
This highlights the growing intersection of sports analytics, computer vision, and digital twin technology, which is transforming how fans and teams interact with game data.
3D reconstruction using player tracking data
A lot of us saw the cool World Cup data visualizations going around social media, like this one from Alexander Bogachev :
I wanted to make my own but go a lot deeper, so I went looking to see where the data comes from.
It turns out a bunch of companies sell data to sports teams and gamblers that they build using computer vision on live broadcasts . It works something like this:
There's a lot more complexity around event tagging and player tracking, which requires visual embeddings for the players to maintain a best guess of their position when their jersey number isn't visible, but this is the high level.
The completeness of this tracking data varies by provider. It generally falls into the following categories:
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