The NBA’s digital transformation is a game-changer

The data continuously amassing in the NBA’s cloud lake is also collected from and made available to the NBA store and to merchandising partners, such as Fanatics and Ticketmaster, as is fan survey data. It’s all part of a plan to build up a repository to enable the creation of next-gen AI- and analytics-based features for all parties, the CTO says.

Taking performance to the next level

As for the NBA’s teams, Bhagavathula points to CourtOptix, an application that tracks and analyzes action on the court. The tool, also developed on Azure, packages up data for each team free of charge and distributes it to them to improve their game. “After each game, the teams get a cache of the data and can then use this to gain additional insights and stats for their own analysis,” he says.

Such sports-related analytics initiatives are significantly altering how professional sports are played across a range of disciplines, including tennis, where the International Tennis Federation is leveraging computer vision to help enhance player performance.

Craig Powers, an analyst at IDC, sees no end in sight to that trend.

“Data in the NFL and NBA has changed the way the sports have been played,” Powers says. “In the NFL, strategies that were once thought to be risky are now the norm — such as going for it on 4th down versus kicking field goals or punting. This is the product of analytics — taking decades of NFL play-by-play data and assigning probabilities and point values to each decision.”

Like the International Tennis Federation, the NBA is betting that the increased use of sensors, cameras, analytics, and AI will have a major impact on enhancing player, team, and officiating performance. While players today do not wear sensors during live action games, the introduction of wearable technologies and new types of IoT sensors will no doubt impact data collection and player performance in the years ahead, Bhagavathula says.

The NBA’s partnership with Hawk-Eye, for instance, will yield far more detailed data that will be used by players and teams to improve their play and plan strategies for games.

“It essentially uses skeletal tracking technology to evaluate how high an athlete is jumping, their body posture when making a shot or how they land on their ankle,” the CTO says. “We think this empirical data will actually unlock insight into basketball.”

It is crystal clear that the unleashing of advanced digital technologies such as AI and cloud computing will continue to change how teams, players, and fans participate in the evolving game of basketball — once simply played with a single ball, two hoops, and high hustle players. 

The introduction of digital technologies at arenas, such as contactless concession stands, and the creation of NBA Top Shot — nonfungible tokens sold as digital basketball cards — are having an enormous impact on merchandising and the basketball economy.

IDC’s Powers believes increasing use of analytics, AI, and sensors to build next-generation game plans, assemble rosters, monitor players’ health, schedule player availability, and manage injuries has changed the game forever.

“In the NBA, we’ve seen the three-point shot rise in prominence as the midrange jumper is frowned upon. Why? Because teams have a better understanding of the value of each shot on the floor,” Powers says. “The NBA has taken it a step further by using video to track the exact spot every pass and shot is taken. Coaches and players can more specifically identify their strengths and weaknesses, and this dictates how offenses run and defenses defend. AI uses this data to recommend specific player matchups and tactics.”

While Bhagavathula did not provide comment on the NBA’s plans for generative AI, AI guru Tiago Cardoso, group product manager at Hyland Software, which counts Formula 1 as a partner, says the introduction of large language models (LLMs), such as GPT, have the potential to transform the game and fan experience further.

“Large models can perform generic tasks, so they could identify players, understand actions, tactics. They would be able to recognize how engaged the crowd would be with a play, and it can express all that in the form of text or voice commentary” — a reality Cardoso suggests is just a few years out, adding that LLMs could one day be used to catalog all past televised games to generate tailored highlight compilations based on prompts such as “Show me videos of LeBron James and [Michael] Jordan doing the same dunks,” Cardoso says.

And it’s all made possible by a foundation of well-orchestrated information technology.