A few weeks after spring term wrapped, Penn’s baseball team embarked on a playoff run on the heels of a remarkable regular season. During the opening round of NCAA regionals, in early June, the Ivy League champs were pitching against Auburn. Wharton economics major Emma Segerman W24 — who at the time was interning for the Milwaukee Brewers, doing international scouting reports — was following Penn’s game closely through ESPN box scores and Twitter updates. As a member of the student-run Penn Sports Analytics Group, Segerman had spent the season working with Penn’s baseball program in advanced scouting; she pulled data on opposing teams, summarized their trends and tendencies, and created scouting reports for the coaching staff ahead of every game. At this match versus the Tigers, the coaches had her report with them in the dugout. Also down on the field was another member of the Sports Analytics Group who was tracking data in real time. On this particular night, after outscoring Auburn in 11 innings, Penn notched another accolade: the first Ivy team ever to beat an SEC team. “If you go to enough baseball games,” says Segerman, “you start to love it.”
This passion for America’s pastime — and knack for numbers — is shared by Adi Wyner, Wharton professor in statistics and data science. His enthusiasm dates back to when he was just six years old and reading the backs of baseball cards, but in 2003, the wildly influential book Moneyball, by Michael Lewis, broke open a brand-new industry. The Wharton Sports Business Initiative was established in 2004, and in 2019, the project expanded and rebranded as the Wharton Sports Analytics and Business Initiative (WSABI). Overseeing the program are faculty directors Wyner and Cade Massey, Wharton practice professor in operations, information, and decisions, alongside WSABI director Michelle Young. “With a tradition of finance, Wharton has always been numerically savvy,” says Massey. “We always felt that sports analytics fit well with our strengths as a school.”
Wyner and Massey teamed up with statistics and data science professors Shane Jensen and Eric Bradlow C88 (who is now the vice dean of Analytics at Wharton) to produce Wharton Moneyball Radio on SiriusXM in 2014; since then, hundreds of episodes have been recorded. Topics have covered everything from the probability of drafted baseball players playing — and staying — in the big leagues to a dissection of the unprecedented scoring and winning patterns in the NHL last year. “Our mission is to create content for the community of people who are really interested in understanding sports through a statistical lens,” says Wyner. Nearly a decade later, the “core four” statisticians still conduct multiple interviews every week — adding up to 50 shows annually — with athletes, coaches, analysts, entrepreneurs, and others. “The dialogue is part of the learning,” says Massey. “It keeps us on the cutting edge of what’s going on in and across sports.”
The year 2014 also saw the launch of Wharton Moneyball Academy, an annual summer program in which graduate and undergraduate students teach sports analytics to high-schoolers. The students learn the basics of statistics and programming and have great ideas about how to apply them in sports. With a record-breaking number of applications this past summer, Moneyball Academy is thriving.
Around the same time that Wharton’s programs were getting started, Bennett Rosenthal W85 WG86 was recognizing an opportunity in the sports industry on the other side of the country. Driven by his love for the game of soccer and impressed by the sport’s rapid growth in the United States, the co-founder and director of Ares Management Corporation helped establish the Los Angeles Football Club in 2014. “There was a lot of white space ahead of Major League Soccer and American soccer,” he says. “The opportunity to build another organization from the ground floor was very compelling.”
Momentum in the field continued to grow on the sidelines and in the classroom. In 2015, Wyner was tapped for an ESPN-funded project to evaluate Major League Baseball. When he introduced STAT 4010, or Sports Analytics, in the spring of 2021, the response was so positive that enrollment doubled the following year. That’s because faculty members aren’t just teaching theory; they’ve spent years working with pro teams and sports analytics companies, and their real-world experiences inform the curriculum for the next generation of Wharton analysts.
Which is to say, what’s been steadily building at Wharton is now in full bloom across major league organizations, with alumni working everywhere from the Miami Marlins to the Seattle Kraken and the exploding industry of online sports betting. Students, alumni, and faculty are playing essential roles at the intersection of sports and data, which now impact virtually every aspect of athletics: Analysts construct rosters, strategize tactics against the opposition, ensure ticket holders have a pleasant stadium experience, help fans place real-time wagers, and keep athletes healthy. “I would argue,” says Wyner, “that Wharton is on the cusp of becoming the most accomplished and intellectual thought leader in sports analytics.”
Los Angeles native Ryan Brill WG23 GR25 has only seen Moneyball twice, but he’s YouTubed Brad Pitt’s boardroom speech to the Oakland Athletics scouts at least 20 times. (“The problem that we are trying to solve is that there are rich teams and there are poor teams,” says Pitt, in the role of Oakland general manager and sports analytics pioneer Billy Beane. “It’s an unfair game.”)
Brill, currently a PhD candidate in applied mathematics and computational science at Wharton, started to explore the field of sports analytics while pursuing his master’s in statistics. “Relative to finance or medicine, it’s a tiny field,” says Brill, explaining that this newness brings opportunity. “There’s an overabundance of interesting problems, because not many statisticians or mathematicians have looked at sports data.”
Although Jared Faust C18 understood that a future in data science would require long hours, he also knew he didn’t want to sit at a desk all day. Today, his office is Citi Field in Queens — as manager of baseball research and development for the New York Mets, he helps oversee aspects of their baseball analytics department, from data engineers building out the back end of the technology to pro scouts relying on insights to evaluate talent. Faust says his economics degree influences the way he values players, but it’s his minor in statistics — and learning how to code at Wharton — that applies more directly to his daily duties. “It was invaluable for laying the foundation for what I’d end up doing,” he says. “I was always interested in sports, but I started to learn that it could be a career while at Penn.”
As a student, Faust was so inspired by the possibilities that he co-founded the Wharton Sports Business Summit in 2017, with the help of peers and Michelle Young. The inaugural event featured keynote speaker Josh Harris W86, co-founder of Harris Blitzer Sports & Entertainment, co-owner of professional teams in nearly every major sport, and a vocal proponent of analytics. Since then, the summit has drawn alumni experts every year to share their industry knowledge, including 2019 keynote speaker David Blitzer W91, the HBSE co-founder, who also donated $1 million this year to support WSABI programming.
Though much progress has been made in the world of data science, there’s also a long way to go — and this is especially true for certain sports. “Baseball is so much more advanced,” says Massey, “it’s really kind of in its own league.” (Just look at the number of MLB general managers and team presidents who originally started in analytics: In 2020, ESPN estimated that more than 40 percent of the top execs in baseball’s front offices hold Ivy League degrees with a focus on data-driven decision-making — up from only three percent in 2001.) The big divide, explains Massey, isn’t just whether there are resources in the building — it’s also about how much influence they have. For example, when Steve Cohen W78 bought the Mets in 2020, Faust noticed a serious investment in technology, data, and resources at the organization. “I had the unique opportunity to watch things expand from one of the smaller departments in baseball to probably somewhere in the upper third,” he says. “I witnessed a lot of growth as we were building out all of our tools.”
Baseball has embraced the world of analytics for decades now, but it’s also an easier game to analyze. “Baseball is a series of independent events that make it much simpler to break down,” says Faust. “It’s really batter versus pitcher.” The nature of basketball is also straightforward — plenty of datasets easily defined by points, players, and on-court positioning — and the NBA has accelerated its use of analytics in recent years. Data application gets a little more complicated, says Faust, with football, where 22 players move in free space on the field. And compare that to sports like hockey and soccer, where there’s a low probability of scoring goals; analysts have to identify what, exactly, is valuable to measure besides getting the puck or ball in the back of the net.
Before his time at Wharton, Daniel M. Rooney WG21 was a coach and scout for the Pittsburgh Steelers and saw firsthand how analytics can help to predict and, ultimately, decide an NFL roster and in-game tactics. “I got to see the day-to-day of sports analytics,” he says, “whether it was understanding the data attached to prospects or evaluating the skill sets of current players.” At Wharton, Rooney delved into the field by completing an independent study with Massey and a few other students that examined data tracking and tried to predict where the industry trends would go. “I continue to have a personal interest in the optical tracking side of sports analytics and how we can extract data off of video,” says Rooney. Now, in his role as director of business development and strategy for the Steelers, Rooney is still locked on analytics — though this time, he’s also looking at how they benefit the entire organization (examples: merchandise sales, sponsorship deals). “Business analytics related back to our sport is a space that we’re all looking at,” says Rooney. “Wharton teaches you to be innovative and push to keep your company ahead of the curve.”
As the sports-betting boom has transformed the gameday experience for many fans, it’s also created a surging worldwide market that depends on statistical analysis. “Every single dimension of our business relies heavily on accurate and timely data,” says Amy Howe WG99, CEO of FanDuel. In e-commerce — and specifically for FanDuel, as the largest mobile sports-betting operator, with a 50 percent share of the market — Howe says, it’s critical to have a “test-and-learn” muscle throughout the company. In marketing, for example, FanDuel explores what resonates in specific regions, the effectiveness of an interface, and how to attract new customers while retaining the returning ones. Tools are used to price new betting markets, set the lines, and determine the odds. The company is also employing artificial intelligence to spot potentially problematic play on its platform. All of this, says Howe, is underpinned by analytics and highly sophisticated models that have been fine-tuned over the years.
“There are few industries that are changing as rapidly as this industry is right now,” says Howe. Part of this fluidity is due to ongoing geographic expansion — in other words, keeping up with the latest U.S. states to legalize online sports betting. Navigating these new markets, along with the addition of other sports and categories, is more easily replicated at scale with analytics. “The only certainty we have is more uncertainty,” says Howe. “Companies who can figure out how to build more agile and predictable business models in every facet of the organization will ultimately prevail.”
Joanna Levy C07 WG18, who works at rival DraftKings, echoes the importance of being able to pivot in this industry. “Responding or adapting to change is one of our core values,” she says. As senior director of sportsbook analytics, she focuses on building the right tools and technology to understand customers and improve products for long-term success. “It’s less about what happened yesterday and more about the opportunities of the future,” says Levy, who was once a financial analyst and also served as director of strategy and analytics with the Philadelphia Flyers. She notes that as new markets open, the DraftKings customer profile changes. “There’s a lot of different inroads to look at our customers and engagement,” she says. “Each state provides a bit of a playbook for the next state.”
Genevieve Weikert WG22 had a similar experience with her career trajectory, having spent five years in finance before her time at Wharton. Now, she works on the business intelligence team for the Baltimore Ravens as a manager of fan insights and analytics. “A key part of my role is to be the most knowledgeable person in our organization on our fan base,” she says, adding that her work touches every business department, from marketing and ticketing to the entire game-day experience. Fan surveys, for example, are curated to collect data for a net promoter score: How satisfactory were the concession stands? Was the stadium technology reliable? How easy was the entrance into the game? “I am fascinated by the business of sports,” Weikert says. “Sports franchises are multibillion-dollar brands that in many aspects still resemble small-to-medium-sized family businesses.”
Wyner is especially proud of the research Wharton students do. Their award-winning work is often published in the Wharton Sports Analytics Student Research Journal, which debuted online last year. He helps facilitate their projects with his weekly research seminar, which formed organically back in 2017 due to many conversations during office hours with Faust and Eric Babitz W18, who’s now director of baseball operations for the Milwaukee Brewers.
Every Friday, a group of students joins Wyner to talk shop: papers, analytic tools, recent news. In the past, that included Sarah Hu W23, whose concentration was in finance and statistics. She had three internships in pro sports while at Wharton: with the Detroit Lions, the New York Knicks, and the Philadelphia Eagles, leading up to their 2023 Super Bowl. “I worked with two football teams,” she says, “and even within a league, it’s so different as to how much they bought into analytics.” Massey points out that when the sports industry has success stories in analytics — like an impressive Super Bowl run — the industry as a whole benefits: “The Eagles have been recognized as one of the most analytics-forward teams in the league,” he says. “Their success in recent years has been a real boon for analytics.”
Wyner and Brill have worked together on several research projects, including a paper that rethinks the metrics used to determine the greatest starting pitchers in MLB history. Their work captured the incredible legacy of Dodger and Hall of Famer Sandy Koufax — not only did he pitch more, but he pitched complete games and didn’t allow many runs. “People who followed Koufax closely knew that 1966 was his best season,” says Brill. “But there hasn’t been a stat, until now, to actually say that was the best ever.”
Brill, like many Wharton students, is a multi-sport mathlete when it comes to research: In football, he created an algorithm that’s been close to perfect in predicting the NFL MVP. He’s also working on a deep study of win probability models and fourth-down decision-making with Wyner. “Many in football analytics consider it an already ‘solved’ problem,” says Brill. “But when we release our results, the public is going to get a kick out of it.” Over the summer, the Philadelphia Union and WSABI began a research endeavor utilizing a few terabytes of performance data; the goal of the project is to extract information from an incredibly high level of detail. (Think: position of the body and points on the ball.) “No one has even drilled past the surface of this data,” says Wyner. Although soccer is still on the ground floor with analytics, it’s slowly adapting to new tools.
LAFC’s Bennett Rosenthal has a front-row seat to this transition. He says there’s a growing conversation around analytics in soccer, and that data is being used in areas like adjusting team play, analyzing opposition, and scouting players: “It gets more impactful every day as the quality of data and the ease of analytics progress.” There’s also a willingness for players to adapt their game. “Teams understand the value in working for higher-value shots,” says Rosenthal, explaining that players are passing up low-value kicks from way outside the box for attempts that are closer to the net, which have a higher success rate. (This is no different from how NBA players have changed their shot profiles to take more threes instead of settling for long twos.) But there’s still work to be done, says Rosenthal: “We’re going to have to figure out more creative ways and more detailed analytics around how we look at both offense and defense.”
As the business of sports becomes increasingly data-driven, dialogue between colleagues and throughout the analytics community is essential. “As analysts, we spend a lot of time looking at data and numbers,” says Weikert. “It’s a critical skill to be able to distill data into compelling business cases. Without great storytelling, excellent data goes unused.” Data scientists read up on their peer research, talk to other experts in the field, and aren’t afraid to test out a good idea that originated in an entirely different league. Massey says these communities have “porous boundaries,” which is one of the reasons sports analytics has grown.
For sports leagues, Faust adds, it will be exciting to watch how analytics will be used to protect the health of athletes through injury prevention and analysis. This is especially true for baseball, where players are prone to specific injuries. Figuring out how to avoid, say, pitcher’s elbow or help athletes recover faster will be key. “It’s the place where all analysts in sports are trying to get,” says Faust. “How can we better protect the assets to our organization?” Rooney agrees that injury prevention is a major motivation for the data. Like many other sports organizations, the Steelers have wearable devices on their athletes to track what and how much they’re doing. “It’s always great to see how fast a guy is running, but the main interest is in sports medicine,” says Rooney. “It’s all about getting our players to the stadium on Sundays.”
As for Emma Segerman? She graduates next year and is intrigued by the potential for analytics internationally, from baseball hotbeds in Latin America and Asia to developing areas like Africa, Australia, and Europe. “There’s a lot of talk about how there’s not a lot of advantage left to gain in baseball, but I don’t think that’s true,” she says, perhaps also speaking to the vast potential for number-crunching across most sports and around the world. “I don’t think the industry is even close to figuring it out.”
THE NEXT FRONTIER
The global sports analytics market size is projected to grow from $3.78 billion this year to $22.13 billion by 2030. Here’s how Wharton and alumni in the industry are positioning themselves at the forefront.
The College Try
Look for more NCAA programs to leverage analytics. This year, Adi Wyner and Massey have signed on to lead a bigger collaboration with Penn Athletics; students already work with several programs including football, field hockey, and baseball.
“I’m excited about how football analytics, from a fan perspective, is going to continue to impact our game,” says Daniel Rooney. NFL’s Next Gen Stats, for example, shares live data of players with fans during the game. Adds Genevieve Weikert: “The data and tools we utilize to enhance and personalize the fan experience will only continue to get better.”
Studies have shown that the field of sports analytics is overwhelmingly white and male, but efforts to diversify are having an impact. Tegan Bunsu Ashby C10, who works in software engineering for the Philadelphia Phillies, co-founded the Women in Sports Data symposium last year to increase the profile of females in the industry. Sarah Hu attended the event and was inspired by the room: “It gives me hope that there are so many women out there who are interested in this field.” Additionally, as part of Wharton’s “Analytics for All” initiative, a version of the Wharton Moneyball Academy curriculum is being developed to be accessible and affordable.
The biomechanical revolution is underway, and the tracking of body movements will get even more precise in the future. “Quarterbacks are developing their game in ways like never before,” says Cade Massey. And wherever technology wasn’t applied before — i.e., in quantifying the explosive traits of successful offensive lineman, a group that’s been mostly understudied — it will now be more prevalent.
Amy Downey is the editor of Lafayette magazine.
Published as “Changing the Game” in the Fall/Winter 2023 issue of Wharton Magazine.