The future of sports is data driven, and analytics is reshaping the game

Gone are the days of grizzled scouts with binoculars scouring ballfields and gyms for plucky young athletes interested in making a name for themselves in their field. They used the “eye” test and trusted their gut when determining if they found their next big star.

Now, scouts and recruiters are using data to determine which athletes are worth a scholarship or draft pick.

Sports analytics — a rapidly growing, high-demand field that blends data analysis with sports strategy — now influences everything from game attendance and revenue to TV ratings and on-field decision-making. Jonathan A. Jensen, associate professor in the Department of Kinesiology and Sport Management at Texas A&M University, said the field’s rapid growth is fueled by the increasing availability and precision of data.

“I think a lot of people think of the movie ‘Moneyball’ as the genesis of sports analytics, but that happened 25 years ago, and what was going on 25 years ago is essentially unrecognizable to what people are doing today,” he said. “We’ve gone from very basic baseball decision making, like what type of player you should draft, to knowing where the ball and every single player is at every moment of every game during every NFL play. That technology changes basically everything.”

Despite the growing reliance on data, analytics does not guarantee outcomes and cannot replace human judgment, Jensen said.

“Not every coach makes decisions based on data — their gut or experience has a lot to do with it,” he said. “It’s still one of the largest discussion points in the industry, and if you turn on ESPN, they are debating gut vs. data-driven decisions. Different organizations have different philosophies, and they’re all applying their unique spin to it and trying to identify the players that work with their formula.”

In years past, young people dreamt of making the team as the star player. Now, with analytics all the rage, the same student could make the big leagues as the number cruncher instead of “QB cruncher” and have almost as much impact on the outcome as the players do.

“There’s so much data available now on the internet,” Jensen said. “That’s been a huge game changer that any student anywhere can essentially — whether you’re in middle school, high school or college — can go on the internet and find data that they can play with.”

“What we need now are students that understand the math, but then can translate the insights for a lay audience or a nonscientific audience. That’s becoming more and more important. You have to have the soft skills, to be able to translate these insights and make people who don’t understand the statistics appreciate them. But then you also have to have the hard skills in terms of understanding the stats. So, you really need both nowadays.”

That demand is driving student interest in sports analytics and related fields. Jensen said Texas A&M is uniquely positioned to be a leader in the field by offering hands-on opportunities that connect students to real-world data and industry professionals and as the home of the Collaborative for Sport Data Science (CSDS), an interdisciplinary coalition of scholars from a number of different academic fields.

“We’ve got the Data Challenge using information for the NFL draft that students can participate in, and we’ve now got a date and venue for our football analytics symposium,” he said. The Football Analytics Symposium at Texas A&M University, or FAST, will take place on Friday, Nov. 13, at the Ford Hall of Champions at Kyle Field. The event will include speakers from multiple areas of football analytics, including on-field, business and human performance, and a panel session featuring analytics experts from NFL clubs.

“It’s going to be a great opportunity for students to share their own research and get input from NFL teams about their work, as well as speakers from across all different fields of sports and business analytics.”

Even for students who don’t pursue careers in sports, data literacy is becoming a critical skill across industries.

“Any company needs data-driven decision making, no matter what you do at that company,” he said. “I’ve had students tell me they ended up talking about their sports analytics class projects in interviews with companies from many different industries.”