INDIAN WELLS, Calif. — Madison Keys remembers when preparing for a match meant hours of guesswork, hunting down grainy footage and manually charting tendencies with a notebook and a pause button.
Now, she can pull up her next opponent’s last 10 matches in seconds, filter by surface, and instantly see patterns in serve placement, rally construction and pressure points. The difference, she says, isn’t just convenience — it’s clarity.
“It used to take five hours just to feel like you had a handle on things,” Keys said. “Now you can get all of that information immediately and actually use it the next day in practice.”
That evolution is at the heart of tennis’ quiet transformation, one driven by data, artificial intelligence and companies like IBM, which has spent more than three decades working alongside the sport’s biggest events. From Wimbledon to the US Open, IBM’s technology is reshaping not only how fans consume tennis but how players like Keys prepare, compete and adjust in real time.
At the BNP Paribas Open in Indian Wells, IBM vice president of sports and entertainment partnerships Kameryn Stanhouse described the company’s role in tennis as both visible and invisible — powering everything from fan-facing apps to behind-the-scenes tools that fundamentally change how the sport operates.
“For more than 30 years, we’ve worked with partners like Wimbledon and the U.S. Open to design and deliver their digital experiences,” Stanhouse said. “But there’s also a side people don’t see — helping organizations scale, become more efficient and turn massive amounts of data into something usable.”
That scale is staggering. A single US Open produces millions of data points, with as many as 156 tracked for every point played across 254 singles matches. What was once overwhelming is now fuel for AI models that generate insights in seconds — from match previews to live win probabilities.
For players, that data is no longer abstract. It’s actionable.
Keys, one of the sport’s most powerful hitters and a veteran on tour, has become what Stanhouse calls a “super user” of the US Open app and similar tools. She uses them not just to scout opponents, but to evaluate herself — often challenging her own instincts with hard numbers.
“I think sometimes our feelings aren’t entirely accurate,” Keys said. “I might feel like I’m hitting the ball great, but then I’ll look at the data and see my speed is down or my RPMs are lower. That gives you something concrete to adjust.”
That feedback loop — data informing decision-making — is changing the rhythm of preparation. Instead of relying solely on intuition or hours of film study, players can now identify specific tendencies and rehearse solutions in a single practice session.
At tournaments like Indian Wells or the US Open, where players often have a day between matches, that immediacy can be the difference between advancing and going home.
“You can go out the next day and work on exactly what you need,” Keys said. “You just feel more prepared.”
Coaches are adapting alongside their players. Darren Cahill, one of the most respected coaches in the game, sees analytics as both a necessity and a challenge — a tool that sharpens strategy but raises the baseline for everyone.
“You can’t get away without doing your homework now,” Cahill said. “The coach’s eye is still the most important thing, but if you’re not combining that with analytics, you’re making it harder on yourself.”
Cahill uses data in two primary ways: to break down opponents and to map long-term development. At the elite level, he said, matches are often decided not by strengths but by the smallest weaknesses — vulnerabilities that only become apparent through deep analysis.
“Everyone has strengths,” Cahill said. “But it’s the weaknesses that get exposed at the highest level. That’s where analytics plays a big part.”
Beyond matchups, analytics allow coaches to build multi-year plans, identifying where a player needs to improve and tracking progress with measurable benchmarks. It’s a shift from reactive coaching to proactive development — one that aligns with IBM’s broader vision of using data to inform every layer of sport.
That vision extends beyond the tour’s elite.
IBM is also working with Cahill and tennis legends Andre Agassi and Steffi Graf on an AI-powered coaching platform designed to democratize access to high-level instruction. The concept is simple but powerful: a “coach in your pocket” that can analyze video, compare technique to top players and deliver personalized feedback in multiple languages.
It’s part of a larger push to bring advanced tools to players at every level — from professionals to juniors — while also enhancing the fan experience.
At Wimbledon and the US Open, IBM has introduced features like “Match Chat,” a conversational AI assistant that answers real-time questions during matches, and “Likelihood to Win,” a dynamic projection that updates after every point. The goal is to turn passive viewing into interactive engagement, giving fans deeper insight into momentum swings and match dynamics.
For players, those same technologies often serve a different purpose.
“What fans see is just one side of it,” Stanhouse said. “We’re also helping players understand their opponents, helping coaches plan, and helping organizations manage everything more efficiently.”
One example is AI-generated match summaries, which allow tournaments like the US Open — where a small team of reporters must cover dozens of simultaneous matches — to produce content at scale. Reporters can then refine and publish those summaries, increasing productivity while maintaining editorial oversight.
“It’s about augmenting people, not replacing them,” Stanhouse said. “Giving them tools to do more.”
Keys sees similar potential in areas like wearable technology, which can track physical stress, predict illness and provide insights into recovery. While not yet universally allowed in competition, she believes the benefits could extend beyond performance to injury prevention — and even fan engagement.
“It could be really interesting for fans to see what we’re going through physically during a match,” Keys said. “I think there’s a lot of potential there.”
That intersection — where performance data meets storytelling — is where IBM’s work in tennis mirrors its broader role in sports and entertainment. The company’s recent partnerships span Formula 1, UFC and the Grammys, all built on the same foundation: using AI to translate complex data into meaningful experiences.
In tennis, that translation is happening in real time, point by point, match by match.
For Keys, it’s simply part of the modern game.
“The access we have now is incredible,” she said. “But it also means everyone else has it too. You have to keep evolving.”
As the sport moves deeper into the AI era, that evolution is becoming the norm. Preparation is faster. Insights are sharper. And the line between instinct and information is thinner than ever.
At Indian Wells, under the desert sun, it still looks like tennis. But behind every serve and every rally is a growing layer of intelligence — one that’s changing how the game is played, coached and understood.
And for players like Madison Keys, it’s no longer the future.
It’s the present.
