IBM launched limb tracking at this year’s U.S. Open – and it’s scoring every tennis player’s serve for fans to see
When world number three and top-ranked American tennis player Jessica Pegula stepped up to the baseline to serve against Belarus’ Aryna Sabalenka in the semifinals at the U.S. Open on Thursday night, it wasn’t only cameras from fans, broadcasters, or journalists capturing her every move.
TL;DR
- IBM launched a 'serve quality' feature in the U.S. Open app, using AI and limb tracking from over 20 body points.
- The feature scores serves out of 100, analyzing movements like knees, wrists, and elbows, processed by IBM's WatsonX.
- This is the first time a Grand Slam tennis tournament has offered such a fan-facing feature, powered by AI.
- The technology uses data from 12 cameras around Arthur Ashe Stadium and builds on Hawk-Eye's 'SkeleTRACK'.
- The USTA and IBM aim to provide fans with digestible insights into player performance, with potential to track other shots and expand to other sports.