Data often informs the way we consume and relate to sports, and since the publication of Michael Lewis’s Moneyball sports leagues, teams and fans have all become more aware of the inherent capabilities of sports analytics.
For instance, you probably know that there are a series of algorithms and analytic programs driving your live gamecasts and fantasy football projections, just as there are a host of 1’s and 0’s determining the advertisements during your live stream.
But according to Nick Maywald of Genius Sports, there is more data being used in sports than you know, and in ways you could never imagine.
“There is an enormous amount that goes on behind the scenes that the average fan definitely would not be aware of,” said Maywald.
To best understand this background data, Sam Ebb, co-leader of the upcoming 2017 MIT Sloan Analytics Conference, says we can consider the two main ways we interact with sports data as individual phenomenon.
First are the data sets and analytic techniques that inform business decisions.
Jim Tobin, National Sales Executive of SAS Sports, says one of the best examples of data-informed business decisions is the New York Mets recent decision to alter their weekend schedule.
“For years they always thought that families that went to Citi Field wanted to go to 1 pm afternoon games,” Tobin said. “After researching and analyzing the data, they found that families preferred to go to games in evenings on weekends, not during the day. So they changed their marketing platform to support that.”
In order to make this decision, the Mets needed to understand a digitally connected and involved fanbase.
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“Fans are definitely more empowered and connected than ever before,” said Tobin. “They have access to information that spans across multiple channels and can be accessed anytime across multiple devices. Fans have the ability to collect information on-demand, especially related to where to buy tickets or merchandise, from whom and for how much.”
So to both meet fan expectations and gather the necessary information, teams and leagues need to understand fan habits and lifestyle preferences as well as predict future behaviors. This type of fanbase comprehension has become one of the major ways that teams and leagues use data to inform their business practices.
Major League Soccer (MLS), for example, has been using SAS to collect data from their individual clubs with the goal to create a centralized data warehouse so that the clubs can analyze and predict customer behavior, allowing them to better serve and better market to their individual fans.
MLBAM, meanwhile, uses SAS to target specific fans who are more likely to cancel their season ticket packages.
“They score their season ticket database with SAS to predict season ticket renewals and determine which fans are more likely to churn,” said Tobin. “It’s valuable information that individual teams can leverage in their sales and retention efforts.”
Another way teams and leagues are using data to inform marketing practices is with targeted advertising. Nick Stamm, director of marketing and communications at Sportradar US, explains:
“If Anthony Rizzo or Kris Bryant hits a home run during the World Series, the power of promoting a Cubs hat or their jersey in the moment of the home run is so much more powerful than just a random MLB paraphernalia ad or a digital banner that isn’t connected to the game action,” said Byrd.
Just as data helps inform business decisions and marketing practices, data also allows coaches and scouts to make front office decisions.
Benjamin Alamar, director of sports analytics at ESPN, says one example of front-office data use is Stanford University’s use of virtual reality to train its quarterbacks against particular defenses. Vijay Mehrotra, a professor of business analytics and information systems at the University of San Francisco, elaborated that at the heart of these simulations is data.
“Analytics are buried in the design of that simulation,” said Mehrotra. “It crucially depends on it.”
Tom Davenport, a research fellow at the MIT Center for Digital Business and a professor of IT and Management at Babson College, says this sports analytics movement in a front office capacity began with baseball and was slower to catch on in sports like basketball, football and hockey, sports with greater interdependency between players.
Sam Ebb of the MIT Sloan Analytics Conference echoed Davenport’s sentiments, and expanded.
“Different leagues have moved at different rates,” said Ebb. “Some of that is because of things that are difficult to quantify, so for a while people have had a hard time quantifying goalie metrics in hockey, whereas a sport like baseball where you have more isolated events and less interdependencies in the data there was a little more kind of initial success in the ease of analysis and the computational intricacy in pulling it together.”
Now, thanks to technological advances, particularly in player tracking, more advanced analytics are possible.
“You [now] know about distance run, speed, burst speeds, impact, strength, recovery times…there’s more and more capability to analyze not just present stats but an enormous amount of historical stats which then creates a whole new range of benchmarking opportunities for performance and coaching,” said Maywald.
But according to Maywald it could cost a top tier European football team upwards of 100,000 dollars to run standard analytics for a single season, and few teams can afford such services.
To take advantage of the available analytics, teams and leagues often turn to data businesses like Genius Sports and Sportradar – companies that can tailor programs and services to meet individual needs.
“If you’re sitting on the sports side, the purpose of Genius Sports would be very much to help them collect sports data, particularly live statistics but also a range of other federation league services around membership and helping them manage their federations and competitions more effectively,” said Maywald.
This means that a team can do everything from analyze player biometrics to enhance scouting reports and help players better prepare for opponents with data-informed virtual reality systems to tailor their marketing to a single fan’s interests and ensure that fans are engaged with the most relevant, exciting possible experiences.
So when Genius Sport’s Maywald says there’s more going on than the average fan is aware of, he isn’t exaggerating.