IBM's AI-Powered Serve Quality Tracking Debuts at U.S. Open, Offering Fans Unprecedented Tennis Analytics

At the recent U.S. Open, IBM, in collaboration with the United States Tennis Association (USTA) as part of their continuing partnership, unveiled a groundbreaking fan-facing feature: "serve quality" tracking. This innovative technology, integrated into the official U.S. Open app, provides spectators with detailed insights into the serving mechanics of every singles player competing in the tournament. The system employs cameras to meticulously track over 20 specific points on each athlete's body, focusing on critical areas such as knee, wrist, and elbow movements. This data is then processed by IBM's sophisticated WatsonX artificial intelligence platform, which calculates a "serve quality" score, rated out of 100. This marks a significant milestone, as it is the first time a Grand Slam tennis tournament has offered such a granular level of biomechanical analysis directly to its audience. While limb or skeletal tracking has found applications in other professional sports, including soccer, its implementation in professional tennis for fan consumption is novel.

The "serve quality" feature is part of a broader suite of AI-driven enhancements introduced for the 2026 U.S. Open event. These additions aim to deepen fan engagement and understanding of the game, including an AI chat function and the automatic highlighting of "key moments" within matches. IBM has indicated that the development of this advanced feature involved private testing over the preceding couple of years, ensuring its accuracy and reliability. By the conclusion of this year's tournament, IBM projects an astonishing analysis of approximately 1.2 billion joints. Furthermore, the company anticipates that the app will generate around 7 million individual "serve quality" insights, offering a wealth of data for fans to explore.

Fans can access these detailed analyses through the tournament's app. By navigating to a specific match, selecting "match recap," and utilizing IBM's "match chat feature," users can pose questions like, "How did serve quality affect the match?" The AI then provides a comparative response. For instance, in a semifinal match, the AI might highlight that Jessica Pegula, ranked world number three and the top American player, achieved a serve quality score of 72.32% against Aryna Sabalenka's 71.95%, even if Pegula ultimately lost the match. This innovation underscores IBM's strategic focus on leveraging artificial intelligence to transform sports analytics and enhance spectator experiences, building upon its long-standing relationship with the USTA.