Unlocking the Next Level of Fan Engagement and Game Performance Through Data and Computer Vision

ByPhyllis R. Edwards

May 27, 2022 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

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The game itself might look very familiar but the way sport is being experienced has undergone a technological revolution over the years – change that has been felt everywhere.

In officiating, a referee is no longer alone, with sophisticated technologies aiding in decision-making. In coaching too. With two minutes to go in the fourth quarter of a game, a basketball coach can find out instantly where a shot is most likely to come from, or where players like to run, from comprehensive, readily accessible information.

Sophisticated camera technologies and detailed video analytics are enhancing the understanding of sport, assisting in the scouting of players, helping sports teams perform better and increasing commercial opportunities. In a world where the hottest technology topic in every boardroom is web 3.0, sports organisations are not far behind.

Data and frontier technologies are pegged as the key drivers of innovation in sports and a key focus for industry leaders. Computer Vision, Artificial Intelligence, and Machine Learning are revolutionising every aspect of sport.

Applying these technologies in major sports such as soccer, tennis, basketball, ice hockey and others shapes newer fan solutions and unlocks the next level of fan engagement.How sport is being played, coached, commercialised and experienced is changing – all around the world.

At the same time technology is creating efficiencies. Automated camera systems enable live matches to be captured with minimal human input, enhancing live-sports production capabilities. By combining AI and real-time athlete data, it is now possible to make predictions of a football goal before it even occurs.

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.

Why computer vision is a gamechanger

In any business, the more data you have, the better you can understand your market. 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.

And with computer vision, sports organisations and leagues can harvest more data points versus a live human being. Then, computer-vision-enabled multiple datasets can be leveraged in a variety of ways, allowing for the data to be contextualised.

Whether it be to share with a team, attract the next generation of fans, or to prompt fans to come back and watch the match, it is driving the future of fan engagement. By marrying in-game data with the metaverse, bringing together the offline and online worlds, we can create a virtual-reality space where fans can interact with each other. 

Delivering superior fan experiences

Packaging and delivering real-time match-related data can truly push fan excitement to the next level. Sportradar is the exclusive provider of National Basketball Association data worldwide to help fans across the globe engage with NBA, WNBA and NBA G League. How it works is that we secure a package of data from the NBA, while we have a mix of automated technologies and on-site sports operators collecting match data in real time.

Sports consumers now routinely expect access to relevant live and historic match-data presentations and visualizations. This is especially so among younger generations who have become accustomed to having a second screen on hand while a game is taking place. Integrating second-screen data on demand into the viewing experience has become commonplace and a general appetite for such data is only likely to swell due to the expansion of the statistics-heavy daily fantasy sports.

But with enhanced capabilities come increased demands. Consumer tolerance for technical failure has decreased dramatically in recent times, and this will only continue. The exponential rise in expectation levels represents a significant challenge for any company working within sports data and covering hundreds of thousands of games in real-time with sub-second latency.

Sportradar’s NBA/WNBA/NBA G data can be consumed by fans on their screens with low latency. There are markets in which fans also enjoy in-play betting. Apart from the on-ground action, we also take into account what the referee’s verdict is, which is what makes this entire process of data collection complex – one where accuracy is absolutely crucial. For example, betting operators rely on the accuracy of our data since the payouts are instant and even a tiny error can have serious implications.

The future of sports driven by data intelligence and technology

With over 20 years’ 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. 

Technologies on wearable devices, tagged equipment and tracking have enabled the generation of more than one million data points for each match – and that is only on the field. These numbers will continue to increase, but the challenge will be to identify data that make a difference in terms of enhancing not only the viewing, but also the overall fan experience by offering accurate, real-time information.

The future of data collection, packaging and delivery will be driven by low latency times. The application of futuristic technologies to solve latency problems will become more prominent. Computer vision will be complemented by new and innovative ways of automating data collection.

We would also see computer vision being used to assess fouls committed on the pitch by automatically mapping player coordinates based on movements. Tooling, powering and supplying the sports market with these technologies will be the main growth areas in the next two years. The sports industry will certainly witness an increased demand for AI specialists, computer-vision experts and data scientists.

Soon, we will also need to think and establish how all of this will tie seamlessly into the metaverse, the cross connections with new and social media, and making sports-information targeting more effective.

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