More Than a Game: How Analytics Gives Sports Teams and Brands a Competitive Advantage (Part One)
By Professor Eric T. Bradlow (@ebradlow) (GBK Collective and the Wharton School)
Earlier this month, I had the pleasure of joining Wharton's latest Beyond Business panel discussion, “More Than a Game: How Analytics Gives Sports Teams a Competitive Advantage”, moderated by Wharton Dean Erika H. James with co-panelist FanDuel CEO and Wharton MBA alum Amy Howe.
In this two-part blog series, I recap the key topics we explored on the panel – from how sports teams use data science to gain a competitive advantage to what businesses can learn from sports analytics (and vice versa). We also discuss why taking a lean data approach is essential, how leaders across sports and business can use data and analytics as a decision-making tool, and why “gut instinct” and judgment still matter.
The Evolution of Moneyball
When the story of Billy Beane and the 2002 Oakland Athletics was first chronicled in Moneyball, Michael Lewis’ best-selling book and subsequent movie starring Brad Pitt and Jonah Hill, applying evidence-based data to assemble a competitive baseball team was a relatively new concept.
Fast forward to today and analytics has become a vital part of nearly every sport. For example, in horse racing, the size of the horse’s heart is a primary driver of predictions or outcomes based on analytics, whereas in soccer analytics, we look at the amount of space created by a player in addition to (to provide greater definition) than simply what he/she scores or assists on.
While Moneyball helped spark broader interest in sports analytics, in some ways I think the movie has made people think too narrowly about how data analytics can or should be used in sports. Player evaluation and fielding a competitive team are only part of thousands of other applications of analytics in sports from AI and video to the use of biometric sensors to assist with training, injury prevention, and motion tracking.
How many of us watch our favorite NFL team, only to scream at the TV to go for it on 4th and two?! Analytics has become an ingrained part of our sports and culture with new emerging applications coming out every day. We are only now just scratching the surface of what’s possible.
Photo credit: Unsplash
“How many of us watch our favorite NFL team, only to scream at the TV to go for it on 4th and two?! Analytics has become an ingrained part of our sports and culture..”
Sports analytics as the great equalizer
As a Vice Dean of Analytics at Wharton and co-host of the SiriusXM Wharton Moneyball podcast (with my fellow Wharton Professors Shane Jensen, Cade Massey, and Adi Wyner), we get to interview leaders across professional sports every week about how they are applying data and statistics on and off the field. To me, sports is a trojan horse to talk about all kinds of interesting analytical problems that business leaders grapple with every day.
A question we have often discussed on Wharton Moneyball also came up on our panel: how big of a competitive advantage does sports analytics really play in leveling the proverbial playing field?
In the early 2000s, when I started working with the Philadelphia Eagles, the team was one of the first NFL franchises to have a data science group. Today everyone has a data science group, so the differential advantage that you can create with analytics has even become more competitive, prompting teams to use more advanced techniques.
Without a doubt, the best coaches, scouts, and teams use data and analytics to make decisions on the field. The second thing great teams do is measure impact. How big of an effect does analytics have on the field?
Creating a competitive advantage or driving impact for analytics always starts with asking the right questions. And this is something I discuss with my students at Wharton all the time. Lots of people can build algorithms, but often they're not asking the right questions.
How analytics has changed the business side of sports
In addition to changing the way teams approach scouting, games, training, and other areas, data and analytics have dramatically transformed the business side of sports. From effectively tracking customers over time to understanding their customer lifetime value to predictive models that optimize ticket sales, sponsorship values and pricing, data science and analytics is a key decision-making tool for teams and organizations.
My fellow panelist Amy Howe, CEO of FanDuel shared how they have built their entire company and first mover advantage in the sports betting industry by applying better data and analytics to predict the outcome of games, identify value in the betting market, and optimize marketing investment and their approach to responsible gaming.
Photo credit: Getty Images
“Sports leagues [such as the NFL] are playing a more powerful role in helping teams access data… to analyze it in a consistent way.” - FanDuel CEO Amy Howe
"At the end of the day, our entire business is about getting our people to make informed decisions, and to do that, we need to give them the data, the information, the analytics to make those decisions," said Howe. “We utilize data in the obvious ways most would expect -- informing our risk and trading decisions and our approach to marketing and media measurement. However, we are now embracing deeper data sets with testing of machine learning to help us spot unsafe or illicit play faster and with more certainty – providing a layer of consumer protection we believe vital to building a sustainable business.”
“Sports leagues also are starting to play a more powerful role in helping teams access data. For example, the NFL has created an integrated platform that pulls all data together on ticketing, food and beverages, and merchandising to analyze it in a consistent way across teams. To be able to look at that and analyze that in a consistent way across 32 different NFL club teams is pretty remarkable."
What businesses can learn from sports analytics (and vice versa)
While sports teams are still lagging behind many major corporations (in terms of total investment in data science), there is much that businesses can learn based on how analytics is applied in the sports world.
One area where sports teams have excelled is the application of real-time data in training and on the field. Another area is the use of integrated data, specifically transactional data, performance data, and customer demographic data tied to anonymized CRM data. Regardless of industry, every company should have this "holy trinity" of data to understand and optimize the customer experience.
“Personalizing the customer experience and removing friction from the user experience is another area where businesses can learn.” - FanDuel CEO Amy Howe
“Personalizing the customer experience and removing friction from the user experience is another area where businesses can learn,” said Howe. “Another area is test and control. Every day FanDuel runs tests to figure out what features should we launch, what's working, and what's not working. The test and control piece, which is fueled by data and analytics, is a really critical part of how you optimize the customer experience over time."
In part two of this blog series, I discuss additional takeaways from Wharton’s recent sports analytics panel including how to use analytics as a decision-making tool (even when you’re working with incomplete information and why “gut instinct” and judgment still matter.