CXOToday has engaged in an exclusive interview with Luka Pataky, Senior Vice President – Automated Content (Artificial Intelligence & Computer Vision) at Sportradar
- How do AI and ML contribute to unlocking commercial benefits for the sports industry?
Demand for deeper data is increasingly growing. What used to be enough to enjoy sports is not enough. Data is becoming a commodity and different consumers of sport are presented deeper and deeper analysis in a fight for eyeballs and attention. Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Computer Vision (CV) are enabling us to collect a lot of data and analyse it to create engagement like never before. And it touches every aspect of sports consumption – from players themselves, coaches, and fans. AI increases viewing engagement, helps increase time spent watching and enjoying sports, and creates immersive experiences by blending physical and virtual worlds. Sports leagues can monetise data and these new levels of engagement to grow the fan base and make their existing fan base more loyal and engaged.
AI enables us to collect more data at a fraction of the cost and helps us analyse terabytes of data in no time. Computer Vision technology can capture more than a 100-fold increase in the level of statistics and data from a single event, in milliseconds. It is this extremely fast, deep, and contextualised data that can transform the sports viewing experience for audiences and fuel generative AI algorithms for creating new content. From improving the current ways of capturing and delivering data to the rapid creation of new data-driven products like virtual sports, Sportradar continue to invest in technology and resources to transform the way sports data is being used to revolutionise the industry and enhance fan experience.
- How are AI and data driving fan engagement in sports?
Deeper insights allow fans to get more engaged with the sport by helping them understand the sport at a different level. Data improves the viewing experience and technologies like Computer Vision, which help us understand what we see in a video stream and where the objects are, enable the creation of immersive viewing experiences. Movements and actions of players can be explained by overlaying stats in real time. Machine Learning and Deep Learning takes tracking data and will provide an explanation as to why something happened the way it happened or how big the chance is of scoring a goal from a specific position.
Moreover, solutions like computer-vision-based soccer-goal predictors analyse games visually, flagging situations that are more likely to lead to a goal almost in real-time, with a nominal, millisecond delay. Such predictors can boost fan engagement and allow broadcasters to deliver an enhanced experience. By applying computer vision technology to live streaming, we can create a more immersive viewing experience for sports fans.
The technology turns every video frame into a digital asset, which we can use to transform what the viewers see on their screens. As a result, fans can expect to see dynamic content such as player performance insights incorporated into a live stream and 3D replays from alternative camera angles.
- What are some exciting ways to leverage AI to offer customers a truly personalized sports experience?
Something like personalised sports highlight creation is only possible at scale by using a combination of Computer Vision to detect key moments and Machine Learning to amalgamate those key moments with the fans’ past consumption patterns to deliver personalised and engaging products. While high-volume, high-quality data underpins personalisation, sophisticated artificial intelligence and machine learning are needed to process and analyse the millions of data points required to deliver effective highly targeted marketing campaigns. And even more than that – fans’ preferences, what articles they have read and what matches they watched can all feed into advanced models that can create whole websites or mobile apps tailored to only that one fan.
Take that one step further – 3D tracking data feeds a photorealistic virtual engine to create a broadcast experience for every single fan, which can be enjoyed in a virtual world: pick players you want to focus on, pick angles you want to see and more. This is the ultimate future of personalisation – from tailored and relevant marketing campaigns to completely fan-generated virtual viewing experiences.
- How does Sportradar work with different rightsholders to use AI to deepen fan engagement with sport?
Sportradar is the exclusive provider of National Basketball Association data worldwide to help fans across the globe engage with the NBA, WNBA, and NBA G League. We use advanced AI to feed all the tracking and event data across NBA events to power the experiences of fans. But it is not only what we can do today – we work closely with federations to reimagine the way fans are experiencing the sport they love, and we help federations attract more fans and make them more loyal. That’s our joint objective!
With over 20 years of experience in the sports technology industry, Sportradar continues to innovate and invest in resources to provide faster, deeper, and more meaningful data. These are the key ingredients to unlock future commercial benefit, whether that be for partners looking for competitive advantage; media companies wanting to show in-depth analysis of the reason a team won; and sports fans themselves, who want to understand not only what they have seen, but more importantly, the why behind it.
- How can AI algorithms analyze sports data to provide insights and improve performance?
The more data you have, the more insights you can generate. Continuing to gather more data, harnessing the insights, and applying them throughout their business should be the foundation pillar of a sports organisation’s strategy. Not only are algorithms powerful enough to make sense of enormous datasets, but they are also extremely fast so they can bring insight to fans or coaches in real-time, allowing them to make instant decisions, whether it is a change of tactic or a fantasy prediction.
AI is also extremely useful post-game – rather than looking through all the actions, it can help players, fans and coaches identify specific moments based on analysis of data and uncover patterns that will help improve in future games. Whether it be to share with a team, attract the next generation of fans, or prompt fans to come back and watch the match, it drives the future of fan engagement.
