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Sports analytics is fueled by fans, and funded by teams. The 19th annual MIT Sloan Sports Analytics Conference (SSAC), held last Friday and Saturday, showed more clearly than ever how both groups can join forces.
After all, for decades, the industry’s main energy source has been fans weary of bad strategies: too much bunting in baseball, too much punting in football, and more. The most enduring analytics icon, Bill James, was a teacher and night watchman until his annual “Baseball Abstract” books began to upend a century of conventional wisdom, in the 1980s. After that, sports analytics became a profession.
Meanwhile, franchise valuations keep rising, women’s sports are booming, and U.S. college sports are professionalizing. All of it should create more analytics jobs, as “Moneyball” author Michael Lewis noted during a Friday panel.
“This whole analytics movement is a byproduct of the decisions becoming really expensive decisions,” Lewis said. “It didn’t matter if you got it wrong if you were paying someone $50,000 a year. But if you’re going to pay them $50 million, you better get it right. So, all of a sudden, someone who can give you a little bit more of an edge in that decision-making has more value.”
Would you like to be a valued sports analytics professional? Here are five ideas, gleaned from MIT’s industry-leading event, about how to gain traction in the field.
1. You can jump into this industry.
Bill James, as it happens, was the first speaker on the opening Friday-morning panel at SSAC, held at the Hynes Convention Center in Boston. His theme: the value of everyone’s work, since today’s amateurs become tomorrow’s professionals.
“Time will reveal that the people doing really important work here are not the people sitting on the stages, but the people in the audience,” James said.
This year, that audience had 2,500 attendees, from 44 U.S. states, 42 countries, and over 220 academic institutions, along with dozens of panels, a research paper competition, and thousands of hallway conversations among networking attendees. SSAC was co-founded in 2007 by Daryl Morey SM ’00, president of basketball operations for the Philadelphia 76ers, and Jessica Gelman, CEO of KAGR, the Kraft Analytics Group. The first three conferences were held in MIT classrooms.
But even now, sports analytics remains largely a grassroots thing. Why? Because fans can observe sports intensively, without being bound to its conventions, then study it quantitatively.
“The driving thing for a lot of people is they want to take this [analytical] way of thinking and apply it to sports,” soccer journalist Ryan O’Hanlon of ESPN said to MIT News, in one of those hallway conversations.
O’Hanlon’s 2022 book, “Net Gains,” chronicles the work of several people who held non-sports jobs, made useful advances in soccer analytics, then jumped into the industry. Soon, the sport may have more landing spots, between the growth of Major League Soccer in the U.S. and women’s soccer everywhere. Also, in O’Hanlon’s estimation, only three of the 20 clubs in England’s Premier League are deeply invested in analytics: Brentford, Brighton, and (league-leading) Liverpool. That could change.
In any case, most of the people who leap from fandom to professional status are willing to examine issues that others take for granted.
“I think it’s not being afraid to question the way everyone is doing things,” O’Hanlon added. “Whether that’s how a game is played, how we acquire players, how we think about anything. Pretty much anyone who gets to a high level and has impact [in analytics] has asked those questions and found a way to answer some.”
2. Make friends with the video team.
Suppose you love a sport, start analyzing it, produce good work that gets some attention, and — jackpot! — get hired by a pro team to do analytics.
Well, as former NBA player Shane Battier pointed out during a basketball panel at SSAC, you still won’t spend any time talking to players about your beloved data. That just isn’t how professional teams work, not even stat-savvy ones.
But there is good news: Analysts can still reach coaches and athletes through skilled use of video clips. Most European soccer managers ignore data, but will pay attention to the team’s video analysts. Basketball coaches love video. In American football, film study is essential. And technology has made it easier than ever to link data to video clips.
So analysts should become buddies with the video group. Importantly, analytics professionals now grasp this better than ever, something evident at SSAC across sports.
“Video in football [soccer] is the best way to communicate and get on the same page,” said Sarah Rudd, co-founder and CTO of src | ftbl, and a former analyst for Arsenal, at Friday’s panel on soccer analytics.
3. Seek opportunities in women’s sports analytics.
Have we mentioned that women’s sports is booming? The WNBA is expanding, the size of the U.S. transfer market in women’s soccer has doubled for three straight years, and you can now find women’s college volleyball in a basic cable package.
That growth is starting to fund greater data collection, in the WNBA and elsewhere, a frequent conversation topic at SSAC.
As Jennifer Rizzotti, president of the WNBA’s Connecticut Sun, noted of her own playing days in the 1990s: “We didn’t have statistics, we didn’t have [opponents’] tendencies that were being explained to us. So, when I think of what players have access to now and how far we’ve come, it’s really impressive.” And yet, she added, the amount of data in men’s basketball remains well ahead of the women’s game: “It gives you an awareness of how far we have to go.”
Some women’s sports still lack the cash needed for basic analytics infrastructure. One Friday panelist, LPGA golfer Stacy Lewis, a 13-time winner on tour, noted that the popular ball-tracking analytics system used in men’s golf costs $1 million per week, beyond budget for the women’s game.
And at a Saturday panel, Gelman said that full data parity between men’s and women’s sports was not imminent. “Sadly, I think we’re years away because we just need more investment into it,” she said.
But there is movement. At one Saturday talk, data developer Charlotte Eisenberg detailed how the website Sports Reference — a key resource of free public data —has been adding play-by-play data for WNBA games. That can help for evaluating individual players, particularly over long time periods, and has long been available for NBA games.
In short, as women’s sports grow, their analytics opportunities will, too.
4. Don’t be daunted by someone’s blurry “eye test.”
A subtle trip-wire in sports analytics, even at SSAC, is the idea that analytics should match the so-called “eye test,” or seemingly intuitive sports observations.
Here’s the problem: There is no one “eye test” in any sport, because people’s intuitions differ. For some basketball coaches, an unselfish role player stands out. To others, a flashy off-the-dribble shooter passes the eye test, even without a high shooting percentage. That tension would exist even if statistics did not.
Enter analytics, which confirms the high value of efficient shooting (as well as old-school virtues like defense, rebounding, and avoiding turnovers). But in a twist, the definition of a good shot in basketball has famously changed. In 1979-80, the NBA introduced the three-point line; in 1985, teams were taking 3.1 three-pointers per game; now in 2024-25, teams are averaging 37.5 three-pointers per game, with great efficiency. What happened?
“People didn’t use [the three-point shot] well at the beginning,” Morey said on a Saturday panel, quipping that “they were too dumb to know that three is greater than two.”
Granted, players weren’t used to shooting threes in 1980. But it also took a long time to change intuitions in the sport. Today, analytics shows that a contested three-pointer is a higher-value shot that an open 18-foot two-pointer. That might still run counter to someone’s “eye test.”
Incidentally, always following analytically informed coaching might also lead to a more standardized, less interesting game, as Morey and basketball legend Sue Bird suggested at the same panel.
“There’s a little bit of instinct that is now removed from the game,” Bird said. Shooting threes makes sense, she concurred, but “You’re only focused on the three-point line, and it takes away all the other things.”
5. Think about absolute truths, but solve for current tactics.
Bill James set the bar high for sports analytics: His breakthrough equation, “runs created,” described how baseball works with almost Newtonian simplicity. Team runs are the product of on-base percentage and slugging percentage, divided by plate appearances. This applies to individual players, too.
But it’s almost impossible to replicate that kind of fundamental formula in other sports.
“I think in soccer there’s still a ton to learn about how the game works,” O’Hanlon told MIT News. Should a team patiently build possession, play long balls, or press up high? And how do we value players with wildly varying roles?
That sometimes leads to situations where, O’Hanlon notes, “No one really knows the right questions that the data should be asking, because no one really knows the right way to play soccer.”
Happily, the search for underlying truths can also produce some tactical insights. Consider one of the three finalists in the conference’s research paper competition, “A Machine Learning Approach to Player Value and Decision Making in Professional Ultimate Frisbee,” by Braden Eberhard, Jacob Miller, and Nathan Sandholtz.
In it, the authors examine playing patterns in ultimate, seeing if teams score more by using a longer string of higher-percentage short-range passes, or by trying longer, high-risk throws. They found that players tend to try higher-percentage passes, although there is some variation, including among star players. That suggests tactical flexibility matters. If the defense is trying to take away short passes, throw long sometimes.
It is a classic sports issue: The right way to play often depends on how your opponent is playing. In the search for ultimate truths, analysts can reveal the usefulness of short-term tactics. That helps team win, which helps analytics types stay employed. But none of this would come to light if analysts weren’t digging into the sports they love, searching for answers and trying to let the world know what they find.
“There is nothing happening here that will change your life if you don’t follow through on it,” James said. “But there are many things happening here that will change your life if you do.”
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