IBM's Court 19 processes 2.7 million data points as AI transforms Wimbledon for 730 million fans

Inside IBM's hidden 'Court 19' at Wimbledon

A serve flashes on the Wimbledon scoreboard before the ball stops bouncing. That number comes from a partnership older than most players on court. IBM has been Wimbledon's technology partner for 36 years, since it planted serve-speed radar behind the baselines in 1991. This year the two extended their deal to 2030, Fortune reported. The reach has outgrown the grass. More than half a million people attend over the fortnight, but they are a sliver of the audience. Wimbledon generated roughly 18 billion impressions across its digital channels in 2025. That reached an estimated 730 million people, the All England Lawn Tennis and Croquet Club says. Visits to the site and app rose more than 20 per cent in the past year. Inside 'Court 19' The engine room sits out of sight. IBM's hub, nicknamed "Court 19", lies beneath the 18th grass court. Over the tournament it processes about 2.7 million data points: ball speed, shot placement, momentum swings. It turns them into the features fans tap on the app. For IBM, tennis is not really the point. Wimbledon is a proving ground. Kameryn Stanhouse, its vice-president of global sports and entertainment partnerships, says there is "a real fear around AI" among executives. "Not because leaders doubt they need it," she says. It is that their jobs may be on the line if they get it wrong. A high-stakes stage, the pitch goes, shows IBM can deploy the technology without breaking it. When the machine gets it wrong That fear is not abstract. In 2025, Wimbledon replaced its 300 line judges, a fixture for 147 years, with automated electronic line-calling. The debut was rocky. The system missed three calls in one quarter-final and shouted "fault" mid-rally, forcing an umpire to step in. Jack Draper questioned its precision, and Emma Raducanu called some rulings "dodgy". That system runs on Sony's Hawk-Eye, not IBM. But the episode hangs over every talk about handing match-changing calls to a machine. IBM stresses its own features are "human-led". A governance layer scores confidence and checks for bias before anything reaches a fan. It is a fine distinction, and one a furious fan is unlikely to notice when a screen gets it wrong. Some of the old theatre has gone too. Players once challenged a call, the crowd hushed, and the replay lit up the big screen. Even IBM's "Likelihood to Win", which recalculates odds after every point, drains a little suspense. Stanhouse calls it a fair trade. "Fans argue less about the marginal calls and more about the tennis itself," she says. A shop window for enterprise AI The commercial logic is plain. The global sports market could top $600bn by 2030, Kearney forecasts. IBM is far from the only firm using sport to prove its AI before selling it elsewhere. Stanhouse says a match offers what few enterprise pilots can: huge volumes of live data, under pressure and in public. The productivity pitch is sharper still. To rebuild the app and site, IBM used an accelerator it calls Bob. It migrated more than 15,000 digital assets to a new platform. Work that would take five specialists months took one engineer a month, Stanhouse says. The final transfer ran in 47 minutes. What comes next is more personal and more remote. IBM has already built a Masters golf app for Apple Vision Pro and expects tennis to follow. Quantum computing may find a role too, though IBM says it has not yet found one in sport. Why it matters Wimbledon is a rare public test of whether AI can slot into something people love without spoiling it. A 2025 Capgemini study found 70 per cent of fans want real-time data. Yet more than half fear too much tech erodes the feel of live sport. That is the tightrope. As Stanhouse puts it, no technology will ever call the winner in advance. "Somebody could wake up with a crick in their neck and can't serve the way they used to."

750 million fans and 2.7 million data points: How IBM's AI powers Wimbledon from hidden 'Court 19' | Fortune

When Giovanni Mpetshi Perricard's serve was clocked at 153 mph last summer -- the fastest in Wimbledon history -- the number flashed on the scoreboard before the ball had stopped bouncing. That instant readout traces back to 1991, when IBM first brought serve-speed radar to the Championships, planting radar guns behind the baselines. Thirty-six years later, IBM remains Wimbledon's technology partner, having built the tournament's website in 1995, its app in 2009, and first introduced AI features in 2017. This year, the partnership was extended until 2030 to carry out a new digital transformation plan, designed, in the words of Wimbledon's marketing and commercial director Usama Al-Qassab, to "engage more people in more places, more often, in more meaningful ways." More than half a million visitors attend Wimbledon over the Grand Slam fortnight. Yet they're a fraction of the audience following along on its app. Wimbledon generated roughly 18 billion impressions across its digital channels, reaching an estimated 730 million people in 2025, according to the All England Lawn Tennis and Croquet Club. In the past year, visits to the official Wimbledon website and app increased by over 20% and registrations to myWimbledon grew by 39%. The app operates year-round for ticketing, player services, and member bookings, before traffic surges during the Championships. IBM's hidden technology hub, nicknamed "Court 19", lies beneath Wimbledon's 18th grass court. Over the course of the tournament, 2.7 million data points -- including ball speed, shot placement, and momentum swings -- are processed through the tech facility. For a company like IBM, a partnership with Wimbledon isn't just about tennis, it's a proving ground. Kameryn Stanhouse, IBM's vice president of global sports and entertainment partnerships, tells Fortune there's a "real fear around AI" among executives. "Not because leaders doubt they need to adopt it, but because they know their jobs may be on the line if they roll it out badly," she says. Stanhouse believes that a visible, high-stakes showcase, such as Wimbledon, gives IBM a way to demonstrate it can deploy tech responsibly and reliably. Ensuring accuracy But executive fears about AI rollouts are not unfounded, both fan sentiment and recent missteps suggest the risk is real. A 2025 study by Capgemini found that 70% of sports fans want real-time match data, but more than half worry that too much technology erodes the authenticity of watching sport live. Not every rollout has landed smoothly. In 2025, Wimbledon's 300 line judges, who had been a fixture of the tournament for 147 years, were replaced with an automated electronic line-calling system. The debut was rocky: the system missed three calls during a quarter-final match and, in a separate incident, it called "fault" mid-rally, forcing an umpire to intervene. Tennis players have voiced their doubts. The current fifth-ranked British player Jack Draper has questioned the system's precision, while Emma Raducanu said she didn't fully trust it, calling some rulings "dodgy". That system isn't IBM's -- it runs on Sony's Hawk-Eye -- but the episode hangs over every conversation about handing match-changing decisions to a machine. IBM stresses its own features are "human-led", with a governance layer that scores confidence and checks for bias before anything reaches a fan in real time. It's a distinction Stanhouse is keen to draw, but for a fan watching a technological error derail a match, the difference between vendors is unlikely to register. For years, players could challenge a line judge's call. This would be followed by the crowd hushing and the ball's flight being replayed on the big screen, and it became one of Wimbledon's rituals. Some say the atmosphere has felt colder without it. Even IBM's "Likelihood to Win" -- a prediction tool that recalculates player odds after every point -- removes some of the suspense. Stanhouse sees the trade-off as worthwhile, even if it removes some of the old theatre. "Fans argue less about the marginal calls and more about the tennis itself and how players are performing," she says. Sport as a proving ground for new tech Wimbledon remains the oldest of the four Grand Slam tournaments, steeped in traditions from strawberries and cream to its all-white dress code. That heritage makes any AI rollout a delicate proposition. Al-Qassab argues AI is simply a productivity tool that helps Wimbledon serve different audiences without changing the experience itself. "I'm not convinced that it will alienate people," he says, noting that most spectators still spend matches watching the action, only checking their phones between points. "It's balanced really finely here and it's working very well." Whether that balance holds as its AI features expand further will be the real test. IBM has helped reshape fan experiences at some of the world's biggest sporting events, from Wimbledon to the U.S. Open Golf Championships and the Masters. It's a booming business, and an increasingly crowded one. The global sports market is forecast to be worth more than $600bn by 2030, according to consultancy Kearney, and IBM is far from the only technology company using sport to prove its AI works before selling it elsewhere. According to Stanhouse, sport offers something few industries can: enormous volumes of data generated under pressure. "If the tool works during a match, under maximum scrutiny, it's already survived a harder test than most enterprise pilots ever face," Stanhouse says, adding it "gets executives thinking about how the technology could apply to their own businesses." To rebuild Wimbledon's app and website, IBM used a development accelerator it calls Bob, which migrated more than 15,000 digital assets (articles, photos, videos, and their metadata) to a new platform. Work that would traditionally take five specialists months, Stanhouse says, was done by a single engineer in a month, with the final transfer taking just 47 minutes. "That is exactly the productivity improvement enterprises are straining to evaluate, and Wimbledon is a rare place they can watch it being tested." For Stanhouse, Wimbledon makes the technology tangible. "A lot of people interact with our technology every day and have no idea about it," she says. "Through the Championships, we put IBM technology in people's hands and they're able to feel it." Hyper-personalization and remote experiences are the future of sports fan engagement, Stanhouse says. IBM has already built a Masters app for Apple Vision Pro, letting golf fans watch the tournament in a fully immersive format, and she expects tennis to follow. "It's all about boosting access in a way that doesn't exist with some of these coveted events," she says. Quantum computing could also have interesting applications, though IBM is yet to find a use case within sports. Despite the consistent encroachment of technology into the sporting field, greater personalization, and more powerful prediction tools, the unpredictable nature of sports is what keeps fans engaged. "No one will ever really know who is going to win. Somebody could wake up with a crick in their neck and can't serve the way they used to" Stanhouse says." No technology will ever be an absolute in sports. But that's why we love it, right?"

Why Wimbledon Is the Ultimate Test of Trusted Sports Data

Beneath tennis's oldest traditions lies one of sports' most sophisticated data ecosystems -- and a glimpse of A.I.'s future. Every summer, Wimbledon reminds the world why tradition still matters. The all-white dress code, pristine grass courts and rituals that have endured for generations make it one of the world's most recognizable sporting events. Yet beneath that tradition sits one of the most technologically advanced ecosystems in global sports. Sign Up For Our Daily Newsletter Sign Up Thank you for signing up! By clicking submit, you agree to our <a href="http://observermedia.com/terms">terms of service</a> and acknowledge we may use your information to send you emails, product samples, and promotions on this website and other properties. You can opt out anytime. See all of our newsletters Every serve, rally and point generates millions of data points that increasingly shape how the match is experienced far beyond Centre Court. Live broadcasts, betting markets, digital platforms and A.I.-powered analysis all depend on trusted data to explain not only what is happening, but why it matters. In sports, A.I. doesn't learn from the game itself; it learns from the quality of the information describing it. That's why trusted datasets such as Opta have become increasingly valuable. As artificial intelligence grows more capable, the competitive advantage no longer lies solely in the algorithms themselves. It lies in the depth, accuracy and context of the data feeding them. The biggest shift over the last decade is that data has stopped supporting sports and started becoming part of the product itself. Fans don't just want scores anymore, they expect context, prediction and explanation in real time. Wimbledon offers a glimpse into a much broader shift taking place across professional sports. Data is no longer simply a byproduct of competition. It has become one of the industry's most valuable commercial and strategic assets. From statistics to intelligence For decades, sports data focused primarily on recording what happened. Today's audiences expect something fundamentally different. They want to understand what is happening, why it matters and what is likely to happen next. A.I. is accelerating that shift. Data has evolved from simply documenting the game to helping interpret it. Modern A.I. models can estimate momentum swings, identify tactical adjustments, predict likely outcomes and generate insights while a match is still unfolding. Organizations such as Stats Perform are already applying these capabilities across global sports, helping leagues, broadcasters, media organizations and digital platforms deliver richer analysis, more personalized experiences and more dynamic storytelling in real time. That distinction matters because audiences increasingly move between television, streaming platforms, social media and mobile apps. Every platform is now expected to deliver insight, not simply information. Data on its own doesn't create engagement. It's what you do with it that matters. A.I. gives us the ability to transform millions of data points into stories, context and insight in real time, but only if those insights are built on trusted foundations. Why women's tennis is leading the way Women's tennis offers one of the clearest examples of this transformation. Through its long-term partnership with Stats Perform and Opta, the Women's Tennis Association (WTA) has invested in one of the world's most sophisticated sports data ecosystems. Trusted data now underpins everything from live broadcast graphics and A.I.-powered insights to performance analysis and betting experiences, demonstrating how data infrastructure has become central to building a modern sports property. The results speak for themselves, reflecting sustained investment in broadcast innovation, trusted data infrastructure and digital fan experiences. The WTA reached a record global audience of 1.1 billion viewers across broadcast and streaming platforms in 2024, while tennis continues to attract the highest proportion of female fans of any major sport. That combination makes women's tennis a particularly valuable lens through which to view the future of A.I. in sports. Women's tennis shows what's possible when trusted data becomes integral to the fan experience. It's no longer enough to tell fans what happened -- they want to understand why it happened. That's the opportunity A.I. creates, not just for tennis, but for every sport. A.I. also makes it possible to personalize the same match for different audiences. A casual viewer may want help understanding a shift in momentum, while a lifelong fan may be looking for deeper tactical analysis. The match remains the same; the experience increasingly adapts to the individual. Data has become a commercial asset Every point played at Wimbledon now creates value far beyond Centre Court, feeding broadcasters, sportsbooks, media organizations, sponsors and A.I. models simultaneously, creating an increasingly interconnected attention economy and sports intelligence ecosystem. Historically, media rights were sports' primary commercial engine. Today, the intelligence generated around live competition has become an asset in its own right, creating new products, richer fan experiences and new revenue opportunities. In many respects, sports organizations are monetizing the game as well as the data and intelligence around it. That transformation mirrors a wider evolution across the sports industry. As A.I. makes it possible to personalize analysis for every fan, trusted sports data becomes a commercial product in its own right. The impact extends well beyond the live broadcast. Fans increasingly expect predictions, tactical explanations and contextual analysis before, during and after matches. Platforms such as The Opta Analyst reflect this shift, helping audiences understand not just what happened, but why it mattered. A.I. isn't the product, it's the engine. What determines its value is the quality of the data beneath it. In sports, trust has become the competitive advantage. Trust will define the A.I. era Artificial intelligence is making it possible to produce sports content at unprecedented speed. The challenge is no longer creating content. It is creating content that audiences can trust. For sports, where every insight can influence broadcasts, betting markets, commercial decisions and fan engagement, inaccurate or poorly contextualized data undermines even the most sophisticated A.I. systems. As A.I. becomes more widespread, trusted data won't become less important -- it will become indispensable. We're moving from an era where speed was the competitive advantage to one where trust is. A.I. can generate content in seconds, but it can't create credibility on its own. That still has to be earned through trusted, contextual data, and that's what will separate the leaders from everyone else. Beyond Wimbledon Wimbledon offers a compelling demonstration of where sports are heading, but its significance extends far beyond tennis. Every league, federation and broadcaster is now asking the same question: how do we transform an ever-growing stream of live data into meaningful experiences for increasingly fragmented audiences? That evolution is reflected in Stats Perform's 2026 Sports Fan Engagement, Monetisation and A.I. Trends Survey, which found that 69 percent of sports organizations using A.I. are already producing more content in less time, while 61 percent believe A.I. will become increasingly important for personalizing fan experiences by 2030. Artificial intelligence will undoubtedly play a defining role in the future of sports. But the organizations that succeed won't simply have the best A.I. They will have the most trusted data. Every summer, Wimbledon celebrates the traditions that have defined tennis for more than a century. Yet, in doing so, it also offers a glimpse of sports' future: one where every great moment is enriched not just by what we see on the court, but by how intelligently -- and how credibly -- we understand it. Read more about Stats Perform here: Stats Perform & WTA | Official Women's Tennis Data & Live Streaming

Sportradar's Patrick Mostboeck On Wimbledon, A.I. and the New Economics of Sports Data

While Wimbledon remains synonymous with tradition, the tournament has quietly become a proving ground for A.I.-powered sports data. Patrick Mostboeck, who leads fan engagement at Sportradar, explains why the next battle for tennis will be over the data that shapes how every match is watched, understood and monetized. As Wimbledon unfolds, the world's attention naturally turns to rivalries, upsets and championship runs. But behind every match is an increasingly sophisticated layer of technology that is reshaping how tennis is watched, analyzed and monetized. A.I. has accelerated the evolution of sports data from a back-office resource into a strategic business asset. Today, millions of real-time data points power everything from broadcast enhancements and personalized fan experiences to coaching analytics and commercial partnerships. As governing bodies and technology companies continue to invest in richer datasets, the focus is shifting beyond collecting information toward extracting meaning from it and determining who stands to benefit. That shift is also changing the economics of the sport. Broadcast rights have long defined the business of professional tennis, but official data rights are becoming an increasingly valuable asset in their own right. As A.I. enables richer storytelling, predictive insights and more personalized viewing experiences, the commercial value of live sports data is expanding well beyond traditional applications, creating new opportunities for media companies, sponsors, technology providers and rights holders alike. For Patrick Mostboeck, senior vice president of fan engagement at Sportradar, that transformation is only beginning. While sports data is often associated with betting, he argues its greatest opportunity lies in making tennis more engaging and accessible for fans while creating new value for broadcasters, rights holders and athletes. Looking to the future, he believes A.I. will fundamentally change how audiences experience live matches through predictive insights, personalized content and augmented broadcasts that add context in real time. Observer spoke with Mostboeck about how the commercial value of tennis data has evolved, why official data rights are becoming increasingly strategic and where A.I.-powered fan engagement is headed next. He also unpacks why one of sport's oldest institutions has become an unlikely proving ground for some of its newest technologies -- and why the next chapter of tennis may be defined as much by data as by what happens on the court. Wimbledon is often viewed as one of tennis's most tradition-bound institutions. At the same time, it's becoming increasingly data-driven. How has the commercial value of tennis data changed over the last decade, and what role does A.I. play in that evolution? If you look back over the last decade, I think sports data has undergone quite a development in tennis. If we were to look back at the beginning of this decade, sports data was mostly about standings and schedules -- really the most basic data points. Gradually, over the last couple of years, it has evolved into a tool for engagement. It has evolved into a tool for further commercialization. The main part of this transition has been that, with more and more data points being collected, there was also a need to make meaning out of those data points. This is clearly where artificial intelligence plays a major role, because if you collect thousands of data points every second, it's just not possible for a human [being] or the human eye to collect those data points, but then also make meaning out of them. This is where, clearly, A.I. plays a major role in processing this data, creating a story out of these data points and then also distributing it. A.I. is making it possible to generate richer insights from matches than traditional statistics ever could. What kinds of information are now being captured or inferred that simply weren't possible a few years ago? I think it's all kinds of data points, but to give you some specific examples, I think one thing that's particularly interesting for us, of course, is, on the one side, where the players are positioned on the court, but also where the ball is exactly landing. That feels like quite a trivial thing, but being extremely precise and detailed [about that] is something that I think the world of tennis has worked on for many, many years. Now you see the development that, for most tournaments, large parts of the umpiring [process] are happening without human intervention. The information about where the ball lands and where the players are positioned obviously gives us additional opportunities to use this for fan engagement applications, coaching analytics applications and so on and so forth. Live sports data has become a valuable asset in its own right. Why is tennis data so commercially significant, and who ultimately benefits from that value? Is it tournaments, governing bodies, broadcasters, technology providers or fans? For me personally, the two most important stakeholders are always the fans on the one side and the athletes on the other side, because those are the only ones without whom the whole ecosystem can't really live and breathe. Based on those two stakeholders, I think you can clearly see that fans appreciate additional depth of information and additional context. Using this additional depth of data within tennis really serves the education [of fans]. It really serves the information needs of the fan, so that ultimately the fan becomes more engaged, spends more time with the sport of tennis and, ultimately, this results in commercialization opportunities. And clearly -- and this is where it's kind of a vicious circle -- the more fans engage with the sport, the more they ultimately spend on the sport. This is where, in equal terms, players participate. This is where tournaments participate. This is also where the media industry participates, because the media and entertainment industry can only create a good product if there is strong interest from fans. So it all comes together, but clearly the fans are at the center of the picture for me. Looking ahead, do you see A.I. creating entirely new commercial opportunities around tennis, whether through personalized viewing experiences, new media products or different forms of fan engagement? The biggest opportunity is already here and not just in some too-distant future: augmenting the way fans see and experience the sport of tennis. It's now possible to augment the broadcast, which is typically the way most fans consume tennis. From a sports perspective, we have created a product called 4Sight, which augments the sport of tennis. More specifically, it provides additional contextual data overlays directly on the stream, explaining what is happening during a match, why a specific player is on track to win, why another player is likely to lose and how all this data comes together to provide that context. I think this, on the one hand, gives us the chance to create a more compelling entertainment product. And that ultimately results in fans staying engaged for longer. Wimbledon is synonymous with heritage, while A.I. represents constant innovation. How do you see tennis balancing those two identities without losing what makes the sport distinctive? For me personally, they're doing a great job of keeping exactly this balance. Every year, when I see the way the Wimbledon grounds are presented and how minimal the branding is, but also the impact that some of the brands are able to achieve through that branding -- and, at the same time, all the content creation and value creation in and around the tournament -- I think it's a good example of where we still have potential and opportunities for growth. I think a lot of this commercialization can still be connected with additional, deeper data points. Specifically, [it's about] how brands, companies and different stakeholders associate themselves with the game, find opportunities within it and tell stories through it. This is still one of the great opportunities within the sport. All of us working within this industry can contribute by working closely together to explore that opportunity. Many people immediately associate sports data with betting, but its applications extend far beyond that. Beyond wagering, where do you think A.I.-powered tennis data will create the greatest value over the next five years? The two most immediate use cases are clearly, first, the media and entertainment space. Sports data has a huge opportunity to enrich and enhance the broadcasting and streaming of tennis. If you look at the current landscape of how tennis is broadcast, I think there's still a significant opportunity, across both traditional players and new players, to enhance the viewing experience. I think this is one of the beauties of the sport of tennis. Tennis really has the opportunity to be one of those truly global sports because, if you look at the top 20 or top 50 players, you'll find so many different nationalities represented that there's interest in the sport across virtually all parts of the world. The second area I would highlight is coaching and analytics. Clearly, one of the main stakeholders, and I mentioned this before, is the players themselves, the athletes. For them, understanding the data behind their own performance and performance analysis, and having tools to help interpret that information, is a quite natural next step in this development. Broadcast rights have long been considered the crown jewel of sports media. Could data rights become equally strategic? The answer is absolutely yes. I think, in some ways, we're already on the path to creating these additional commercial opportunities, but for others, we probably don't even know what's possible yet. Personalization of the fan experience is a significant opportunity. But if you think about commercialization through advertising and sponsorship, I think combining those data points -- or additional depth of data -- with brands, and the opportunity to advertise at the contextually right moment, is a significant opportunity. This is truly where sports data, on the one side, and commercialization, on the other, come together to create additional benefits. I think those two areas play well alongside each other. It's always hard to predict how their respective values will develop. Data rights, and the products being developed from data, have a clear path for growth, as do media rights. So, from a rights-holder's perspective -- and from the perspective of the sport -- I think there's a clear benefit to developing both of those areas side by side. If we're having this conversation again five years from now, what do you think will have changed most dramatically about the business of tennis because of A.I.? A crystal ball is always difficult, of course, but I would say that predictive capabilities will become more and more standard across sports, and likely within tennis specifically. At the moment, most of the data we talk about is based on past events or the most recent events. I could imagine a future where much more of the broadcasting and entertainment landscape shifts toward predictive insights -- what is going to happen in the next minute, what's going to happen in the next five minutes -- and that data is then used across all kinds of entertainment applications. Whether it's sports betting, sports media or coaching applications, I think this predictive type of data can be quite useful.