Google Cloud partners with WWT to centralize NBA player performance data

Google Cloud has partnered with World Wide Technology (WWT), a technology solutions provider, to develop an AI-powered playbook for an unnamed NBA franchise, aiming to unify previously siloed data on player performance and health. The collaboration addresses the need for better data interoperability in professional sports, enabling coaches, medics, and sports scientists to make more informed decisions about game strategy and player workloads.

What you should know: The AI platform centralizes data that was previously scattered across different systems, making it easier for team staff to access comprehensive player insights.

• Team members including coaches, medics, and sports scientists will gain access to unified stats on player performances and trends over time.
• The system is designed to track potential injury risks and optimize lineups based on data-driven insights.
• “Without a centralized system or an intuitive way to explore their data, every decision felt like playing defense,” WWT said in a statement.

How it works: The platform leverages Google Cloud’s data analytics and natural language processing capabilities to make complex statistics accessible to non-technical users.

• The system uses Google Cloud services including BigQuery (a data warehouse for storing large amounts of information) and Dataplex (a tool for managing data across different sources) to store, analyze, and access centralized data.
• Google’s natural language tools, including Explore Assistant and Conversation Analytics, enable interactive features that allow users to pose questions in plain English.
• Users can ask natural-language questions and receive instant statistics, such as player trends or performance breakdowns.

The big picture: This partnership represents the latest effort to bring artificial intelligence to professional sports, joining recent AI initiatives across the Tour de France, Formula 1, and Wimbledon.

• The technology is built to scale and integrate new data sources and predictive modeling capabilities over time.
• Teams are seeking answers to critical questions: “What’s really moving the needle on wins? How can we get ahead of risk before it turns into an injury? How do my top players compare to all-stars around the league?”

Why this matters: The collaboration highlights how AI is transforming sports analytics by breaking down data silos and democratizing access to performance insights across different roles within professional sports organizations.