Why AI Is The Next Frontier In Sports Fan Engagement And Revenue
Summer always comes with a lull in U.S. pro sports between the NBA and NHL championships in mid-June and when the highly anticipated NFL season kicks off in September. Baseball, America’s favorite pastime, reliably fills this void, bolstered every four years by the Olympics and the FIFA World Cup.
This year, the Women’s World Cup drew massive attention as the U.S. National Team won its fourth title — a world record for women’s pro soccer. In fact, the American audience for the Women’s World Cup final was and generated massive social media engagement from players, fans and celebrities — a hard act to follow for the MLB All-Star Game a few days later.
Events like the Olympics and World Cup that rally the country around a national team generally drive heavy fan engagement. The same goes for games like the Super Bowl. For regular-season play, however, pro teams are increasingly challenged to find new ways to connect with fans in an interesting era where , but teams don’t need to fill seats to make money. Today, fans have countless ways to watch games, check scores and keep up with teams and players, be it via TV, online/social media or a mobile app. And this digital shift is providing a huge opportunity for sports brands to leverage data to boost engagement and revenues.
The use of data analytics in sports is not new, of course. Anyone who’s ever collected baseball cards (or seen the back of one) knows it’s fundamentally a stats-driven sport. Sabermetrics, the mathematical and statistical analysis of baseball, has been around for decades, and is a member organization comprised of thousands of fans dedicated to the topic of baseball statistics.
Traditionally, this kind of data and statistical analysis was used by managers and coaches to fine-tune their lineups and devise strategies to win more games. In other sports, statistical models are widely used in sports gambling to calculate betting odds and predict winners. However, sports as a fan-based entertainment business is going through rapid digital transformation. The use of data, powered by advanced technology, has evolved beyond statistical analysis into much more sophisticated artificial intelligence (AI)-powered applications. Sports leagues are finding new and creative ways to leverage AI to boost fan engagement and uncover new revenue streams. New data sources from both first-party interactions with fans and through relationships with third-party data sources are making this transition possible.
Social media is one major area of focus for sports, and both professional leagues and individual teams have increasingly turned to AI-powered analytics solutions like Unmetric to drive fan engagement and identify new sponsorship opportunities. Pro sports leagues like the NHL are through Facebook Messenger and WhatsApp to engage with fans with the potential to sell sponsorships and digital subscriptions to a larger fanbase. In this case, AI is used to create efficiencies of scale and free humans up to focus on higher-level strategic brand marketing and sponsorship activities.
Social media will continue to be fertile ground for sports teams as a majority of younger fans — especially NBA fans — turn to social networks to discuss sports news and follow their favorite teams and players. The next frontier of fan engagement involves things like AI-powered content optimization. Wimbledon, for example, has been leveraging AI-powered image and acoustic-based insights from to curate what are predictively the most engaging highlight videos. Imagine the potential to optimize highlights that can ultimately be monetized based on engagement. While tennis is much different than hockey, basketball or American football, similar applications could be used in these and other sports.
Another greenfield opportunity is the application of AI to player skill measurement. This is basically the next level of Sabermetrics and is being applied to sports outside of baseball.
