Celtics director of basketball analytics David Sparks was scrolling through his timeline last summer when he caught a tweet from Seth Partnow, a peer in the field of sports data who was the Milwaukee Bucks director of basketball research before becoming a writer at The Athletic.
Partnow compiled rosters, not of players or free agents, but of analytics staffers for every team in the NBA.
The list put in one place many of the names at the center of the unceasing race for information that has dramatically shifted the way games are played, coached, and viewed.
It also crystallized that, however polarizing the argument about the role of analytics in sports may be, the thirst for people with the ability to process and translate valuable and often obscure data has created jobs around the league that are as coveted as they are scarce.
The list struck Sparks for two reasons.
“I don’t think it’s comprehensive or perfectly accurate,” he said. “But it is not a very diverse list.”
The names and faces driving the analytics movement in the sport are overwhelmingly white and male. When Sparks stepped back and looked, he saw the same picture.
“I think that, going back in time five years, the list would have been smaller and similarly diverse,” he said.
The past 20 years, nothing has reshaped sports at large more than the shift toward quantitative analysis. The standard box score statistics that everyone knows and understands are still there. But the foundation that Bill James laid with sabermetrics in the 1970s became the inspiration for the minds who created the Association for Professional Basketball Research message board at the turn of the century to provide concrete answers for questions that typically came in the form of hot takes.
Many of the names on that message board — from Dean Oliver to John Hollinger — became influential in basketball’s shift toward analytics. What was commonplace in baseball became cult-level cool in basketball and is now an essential part of front office operations across all sports.
But as analytics moves from the fringes to the forefront, it faces the same issues of exclusion as many other fields.
“I can’t point to a specific thing,” Sparks said. “But I would say in the last four or five years, the discussion about lack of diversity in the zeitgeist has increased. I don’t think we’re anywhere near the point where people represented in positions like mine look like the pool of people who would be interested in positions like mine.”
The lack of diversity is possibly most striking at the annual MIT Sloan Sports Analytics Conference, which started as a meeting of analytic minds and has morphed into a big-ticket event, attracting stars across all sports and bringing them to the intersection of data, culture, and innovation.
“You can see it at the Sloan Conference,” Sparks said. “I think pretty noticeably — a lot of people you pass in halls and people giving presentations. It’s definitely changed in the last two or three years, I’d say, for more diversity. But a lot of people there are white guys that look just like me.”
This year, Sloan is sponsoring 10 Black undergraduate students to attend the virtual conference, and has 13 women or people of color among its list of speakers and panelists.
For years, the standard argument around sports and analytics devolved into a nerds-vs.-jocks food fight that largely ignored the reality that technology was making data an inextricable part of the way society functions, and that the inevitable staying power of math and science in sports would lead more organizations to invest in analytics, in turn creating more jobs.
‘“A lot of people there are white guys that look just like me.”’
David Sparks, Celtics director of basketball analytics, on the annual Sloan Conference at MIT
The Celtics have one of the most respected analytics departments in the NBA. It is made up entirely of white men.
The Red Sox loaded their research and development team with talent a year ago. Kayla Mei is the only member of the staff who is not a white man.
Richard Miller, Ernie Adams, and Matt Lindsay make up the Patriots analytics team. They are all white men.
The Bruins team of Jeremy Rogalski, Josh Pohlkamp-Hartt, and Campbell Weaver are also all white men.
Sparks was among nearly 150 sports analytics professionals who participated in “Measurables Office Hours,” a program designed to connect people in the industry with people from underrepresented groups who want to be in the industry. The Celtics also have members of their analytics team working with the Burke High School sports analytics club in Dorchester.
As the country faced a racial reckoning last year in the wake of the killings of George Floyd and Breonna Taylor, many in the sports data community were forced to look in the mirror and examine ways to make a growing industry more inclusive.
Sensing an opportunity
For many, the first step into this niche and insular field is realizing that such careers exist. John Tobias studied criminal justice at the University of North Carolina-Charlotte. In his late 20s, after working in finance, he decided to chase his passion and earned a master’s degree in sports management from High Point. An internship with the NBA’s Charlotte Hornets in 2004 proved to be a turning point.
“That’s when I realized the role of a statistician actually existed,” said Tobias, a Black man.
He took a job as a talent statistician at ESPN in 2013, feeding stats to broadcast teams. He saw how his ability to translate those numbers enhanced the viewing experience.
“My job is to educate the viewer and help explain the narrative,” he said.
Two years ago, Tobias saw that Syracuse University became the first university to offer an undergraduate degree in sports analytics.
“That’s when I said to myself, well, wait a minute,” Tobias said. “If this is what I somewhat do for a living, I would love to have the opportunity to teach students how to do stats and analytics, and let them know not only how important stats and analytics come into play from a TV broadcast standpoint, but when it comes to like evaluating a team, evaluating a player, or even when it comes to contract negotiations.
“So I say to myself, I could really educate students on a lot of things to where stats and analytics can really, like, come into play in the sports world.”
In 2019, Tobias contacted UNC Charlotte and pitched the idea to teach a course on stats and analytics. The course was successful and gratifying, and he taught it again last spring and summer. He was able to get the analytics teams from the NFL’s Carolina Panthers, the Hornets, and the Charlotte Knights, a minor league baseball team.
As satisfying as it was, he also took note of the makeup of his class.
“The one thing that I did notice is that there are very few minorities,” he said.
Looking at the career Tobias has carved for himself, he said he’s a rarity in the field.
“I’ve only seen one other African-American do what I do,” he said. “And of course, that’s problematic.”
Making a connection
As an analyst for Major League Baseball’s Seattle Mariners, Spencer Weisberg felt the same sense of singularity. Part of what drew him to sports was watching Ken Griffey Jr., Jimmy Rollins, and Ryan Howard as a kid.
“I could see myself in them,” said Weisberg, a Black man.
He played sports while growing up, but he also had an uncanny skill for making trades and building franchises while playing the Madden and 2K video games. He also was strong at math. When he was around 10, his mother got him a copy of “Moneyball,” a book that examined the use of analytics by the 2002 Oakland Athletics. He didn’t think much of it at the time.
But the more he read, the more he got into it.
In Weisberg’s words, he thought, “Oh, this is sick. This is a real thing.”
He added, “I never really thought, ‘This is what I’m going to do.’ It was more like, ‘Oh, that’s cool, somebody like me could do that.’ ”
Weisberg went to Cal Poly San Luis Obispo to study computer science with the intention of landing a job that would earn him a lot of money.
“I’m probably not going to like it,” he said. “But I don’t care.”
He had a rocky first year that nearly ended with him failing out, but he found himself in a statistics class that changed his perspective, and ultimately his future.
“I was like, ‘Wow, all this stuff can be applied to sports,’ ” he said.
That connection was all he needed.
“So what I would do was, I would take my statistics class, they’d give us homework, I wouldn’t do the homework,” Weisberg said. “I would just go apply what I learned in class to sports projects.”
Weisberg started to see a path for himself. He began researching baseball jobs and applying. Even though he didn’t know much about the deep analytics of the game, he started an internship with the Mariners in 2019 between his junior and senior years. He threw himself into the work and learned on the fly.
“I think that it clicked for me when I kind of, like, realized I’m passionate about it,” he said.
Weisberg was hired as a full-time analyst in January. The job is rewarding, but he finds himself thinking of ways to create opportunities for people like himself.
He noticed it in school.
“I’m pretty aware,” he said. “It kind of has always been a thing to me that, in college especially, I was like, ‘Everybody in this computer science class is really white. There’s like three girls and me. We are the only people that aren’t white men. I feel out of place.’ ”
‘It’s pretty skewed’
The challenges sports face with inclusion are the same ones science and technology deal with at large. While there are viable candidates from an array of backgrounds, the pool is largely made up of a homogenous demographic. Ben Lindbergh, former editor and chief of Baseball Prospectus and now a staff writer at FiveThirtyEight, pointed to the trend of Ivy Leaguers running baseball front offices and analytics departments.
“If you’re only pulling from those places, then you’re only going to recruit people from certain backgrounds,” he said. “And also, a lot of those people start out in internships that you might not even be able to afford unless you’re fairly affluent.
“And then you have the people running teams — general managers — are almost entirely white in baseball, and it’s pretty skewed in other sports too, so they may have their own biases that lead to certain types of hiring.
“It’s something that I hope will happen more in time just as there’s more of an emphasis on diversity.”
At the heart of the analytics boom is the desire to find an edge over the competition. Much of the data teams have been mining are proprietary. Until recently, analytics teams largely didn’t have a public presence. Teams kept things close to the vest in hopes of finding the next breakthrough. For that reason, Lindbergh said, it makes sense to not be exclusionary.
“If you want fresh ideas, then it makes sense to try to recruit people from a different background, people who might have different experience or exposure to different things and think in a different way than other people think,” he said.
“If everyone you hire comes from the same background, then you might just get some groupthink going on, and then you’re not going to be able to find the next big idea.”
Working toward solutions
For John Drazan, the question isn’t why sports analytics isn’t more diverse, but rather how can the field make itself more diverse?
Alongside John Scott and Jahkeen Hoke, Drazan works with 4th Family, a nonprofit that combines STEM and sports for youth in Albany, N.Y.
Drazan played college basketball with Scott at SUNY Geneseo. While he was working on a degree in physics in 2012, Scott was an assistant coach at Albany High School. Drazan remembers Scott calling him and saying, “Yo, Draz, my kids suck at rebounding and math, and I thought of you.”
Drazan came on board as a volunteer coach, and the first thing he realized was that the players responded to his suggestions if he could explain his rationale.
“I’d say, you need to get to the back side for a rebound, and they’re like, ‘Why?’ ” Drazen said. “I’m like, ‘Well, because statistically, the ball is going to go to the other side of the rim more often.’ And they’re like, ‘How do you know that?’ ”
The Q&A became a project. The players collected data on where rebounds went. When they could see it — using data they gathered themselves — it clicked. Those types of projects became the norm.
In time, the students became fluent in analytics. A project in which students took their own shooting data won Sloan’s award for best research paper in 2017. That recognition led to a partnership with Tomorrow’s Stars Foundation, the outreach arm for the NBA Summer League in Las Vegas, for the court science classroom, a one-week program in which student-athletes learn about sports science and analytics, then present their findings.
“It’s been a really wild ride,” Drazan said. “But it’s been really important and fun.”
While the diversity gap is vast, Drazan believes it benefits everyone if analytics is a language that more people speak.
“I kind of flip it from the perspective of why aren’t more people in it,” he said. “I think that not having diversity in analytics is a huge missed opportunity for empowering and inspiring our diverse American population.”
Julian Benbow can be reached at email@example.com.