How AI is transforming the fan experience
For billions of people, being a sports fan is about community and identity. Some consider it to be what defines them. It is why they cheer for their teams or wear their jerseys. And it is a lifelong journey, marked by strong loyalty and dedication, making this a unique and interesting cohort. But what determines how deeply each one of them identifies with their sport or team has long remained a mystery. What drives their fandom? How committed are they? Are they a casual observer or a superfan? These are key questions for everyone across the sports ecosystem as they try to build new audiences and deepen engagement with fanbases. But, until now, the answers have been elusive. The proliferation of GenAI is for the first time making these insights a possibility, illuminating fans’ own preferences faster than ever before, and with greater precision. This has become possible thanks to two enablers. How fans consume sports First are the changing trends in how fans consume sports, trends that have themselves changed the possibilities for interaction. Namely, the broadcasting shift from linear and cable to digital streaming and the growing consumer expectation for personalized experiences, which address their wants, needs, and interests. In a streaming channel, content powered by standard and generative AI can be embedded on screen. In such instances, generative AI can act as an ultimate sports brain, as if someone who has watched all the games in granular detail and has read every piece of sports content, which combined results in the ability to perform the most insightful level of analysis. This also opens the door to new and refreshed forms of content, such as virtualized replays, data visualizations, and animated overlays, analytics, and explainers. All are delivered in real time and through the application of AI in a hyperpersonalized manner to the individual viewer. Additionally, key elements of the sports viewing experience can be gamified, either through challenges and rewards or frictionless betting opportunities, seamlessly delivered as part of the broadcast. And, increasingly, augmented and virtual reality content is being developed to serve the increasing trend towards digital twins, which are virtual models of a physical object that uses real-time data to simulate and monitor its behavior and performance. The availability of sports data The second enabler is the availability of sports-related data that already exists but can now be supplemented with new data captured at higher speed and ever greater depth. Coupled with AI-powered tech, this breadth of data is the foundation for a new era of products, offerings, and experiences that can facilitate a higher degree of fan engagement. We are already seeing the beginnings of what’s possible. For example, Sportradar’s computer vision tech, gathers 100 times more datapoints than traditional, manual data collection, and all in a fraction of a second. This is providing deeper analysis of the action on the field of play and translates into greater context and richer understanding of what a fan is witnessing. Through AI, sports fans are now being served with new forms of content and experiences. That might mean customized analytics, insights, or interactions, served in real time during the action. It could mean immersive experiences that enhance a fan’s intrinsic sense of community, such as virtual stadium chatrooms and tours. Or it may mean live, interactive, in-game replays or virtualized simulations, viewed from any angle the individual viewer desires. Hyperpersonalized content Together, this establishes a virtuous circle of better and more extensive data, leading to more dynamic and relevant—hyperpersonalized—content and to more passionately engaged fans. What it always means is bringing fans closer to the action. As an avid sports fan myself, this is what I want from my viewing experience and what makes me excited to now be a part of a team, and industry, that is making this happen. Beshad Bezhadi is chief technology officer and chief AI officer of Sportradar.
Business Economic Syndicated News 
For billions of people, being a sports fan is about community and identity. Some consider it to be what defines them. It is why they cheer for their teams or wear their jerseys. And it is a lifelong journey, marked by strong loyalty and dedication, making this a unique and interesting cohort.
But what determines how deeply each one of them identifies with their sport or team has long remained a mystery. What drives their fandom? How committed are they? Are they a casual observer or a superfan?
These are key questions for everyone across the sports ecosystem as they try to build new audiences and deepen engagement with fanbases. But, until now, the answers have been elusive. The proliferation of GenAI is for the first time making these insights a possibility, illuminating fans’ own preferences faster than ever before, and with greater precision.
This has become possible thanks to two enablers.
How fans consume sports
First are the changing trends in how fans consume sports, trends that have themselves changed the possibilities for interaction. Namely, the broadcasting shift from linear and cable to digital streaming and the growing consumer expectation for personalized experiences, which address their wants, needs, and interests.
In a streaming channel, content powered by standard and generative AI can be embedded on screen. In such instances, generative AI can act as an ultimate sports brain, as if someone who has watched all the games in granular detail and has read every piece of sports content, which combined results in the ability to perform the most insightful level of analysis.
This also opens the door to new and refreshed forms of content, such as virtualized replays, data visualizations, and animated overlays, analytics, and explainers. All are delivered in real time and through the application of AI in a hyperpersonalized manner to the individual viewer.
Additionally, key elements of the sports viewing experience can be gamified, either through challenges and rewards or frictionless betting opportunities, seamlessly delivered as part of the broadcast. And, increasingly, augmented and virtual reality content is being developed to serve the increasing trend towards digital twins, which are virtual models of a physical object that uses real-time data to simulate and monitor its behavior and performance.
The availability of sports data
The second enabler is the availability of sports-related data that already exists but can now be supplemented with new data captured at higher speed and ever greater depth.
Coupled with AI-powered tech, this breadth of data is the foundation for a new era of products, offerings, and experiences that can facilitate a higher degree of fan engagement.
We are already seeing the beginnings of what’s possible. For example, Sportradar’s computer vision tech, gathers 100 times more datapoints than traditional, manual data collection, and all in a fraction of a second. This is providing deeper analysis of the action on the field of play and translates into greater context and richer understanding of what a fan is witnessing.
Through AI, sports fans are now being served with new forms of content and experiences. That might mean customized analytics, insights, or interactions, served in real time during the action.
It could mean immersive experiences that enhance a fan’s intrinsic sense of community, such as virtual stadium chatrooms and tours. Or it may mean live, interactive, in-game replays or virtualized simulations, viewed from any angle the individual viewer desires.
Hyperpersonalized content
Together, this establishes a virtuous circle of better and more extensive data, leading to more dynamic and relevant—hyperpersonalized—content and to more passionately engaged fans.
What it always means is bringing fans closer to the action. As an avid sports fan myself, this is what I want from my viewing experience and what makes me excited to now be a part of a team, and industry, that is making this happen.
Beshad Bezhadi is chief technology officer and chief AI officer of Sportradar.
