Sports analysis is facilitated by fans and funded by teams. The 19th MIT Sloan Sports Analysis Conference (SSAC) held last Friday and Saturday gave us more clearer than ever how both groups could join forces.
After all, for decades, the industry’s main energy sources have been fans tired of bad strategies, such as too much bunting in baseball and punting in soccer. The most enduring analytical icon, Bill James was a teacher and night watchman until the 1980s when the annual book on baseball abstraction began to overturn a century of traditional wisdom. After that, sports analysis became a profession.
Meanwhile, franchises continue to rise, women’s sports are booming, and American university sports are specialising. As Michael Lewis, author of “Moneyball,” pointed out in a panel on Friday, it all should create more analysis jobs.
“This whole analytical movement is a byproduct of making decisions a very expensive decision,” Lewis said. “It didn’t matter if you were paying someone $50,000 a year or being wrong. But if you’re paying $50 million, the right thing is better. So, someone who suddenly can give that decision a little more advantage is more valuable.”
Do you want to be an important sports analysis expert? Five ideas gathered from MIT’s industry-leading events show you how to gain traction in this area.
1. You can jump into this industry.
Bill James happened to be the first speaker at SSAC’s opening Friday morning panel at the Hines Convention Center in Boston. His theme: The value of everyone’s work, as today’s amateurs become experts of tomorrow.
“Time makes it clear that people who are doing really important jobs here are people in the audience, not people sitting on stage,” James said.
This year, its audience has 2,500 participants from 44 US states, 42 countries, and over 220 academic institutions, with dozens of panels, research paper competitions and thousands of corridor conversations between networking participants. SSAC was co-founded in 2007 by Daryl Moray SM ’00, president of basketball operations for the Philadelphia 76ers, and Jessica German, CEO of KAGR, the Craft Analysis Group. The first three meetings were held at the MIT classroom.
But even today, sports analysis is primarily grassroots. why? Fans can study sports intensively without being bound by convention, allowing them to study quantitatively.
“For a lot of people, driving is that they want to think about this (analytical) and apply it to sports,” ESPN football journalist Ryan O’Hanlon told MIT News in one of those corridor conversations.
Ohanlon’s 2022 book, Netgain, documented the work of several people who worked outside of sports, made useful advances in football analysis and jumped into the industry. Soon, the sport may have more landing sites between the growth of major league soccer in the US and women’s soccer everywhere. Ohanlon’s estimates also show that only three of the 20 clubs in the English Premier League are deeply invested in the analysis. That could change.
In any case, most people leaping from fandom to professional status are willing to look into issues others take for granted.
“I don’t think anyone is afraid to question the way they’re doing things,” O’Hanlon added. “The way you play the game, how you get players, how you think about something. Anyone who has reached a high level and is affecting them (in the analysis) has asked these questions and found a way to answer some.”
2. Become friends with the video team.
If you love sports, start analyzing it, produce some good work that grabs attention, and – Jackpot! – Be hired by a professional team to do the analysis.
Now, as former NBA player Shane Battier pointed out on the SSAC basketball panel, you still don’t spend time talking to players about your beloved data. It’s not how a professional team works, nor is it a team that is well-versed in statistics.
But there’s good news. Analysts can still contact coaches and athletes through the skilled use of video clips. Most European soccer managers ignore the data, but pay attention to the team’s video analysts. Basketball coaches love videos. In American football, cinema research is essential. Technology has also made linking data to video clips easier than ever.
Therefore, the analyst should become a member of the video group. Importantly, Analytics experts are more aware of this than ever before. This is what SSAC is obvious throughout the sport.
“Soccer videos (soccers) are the best way to communicate and appear on the same page,” said SRC co-founder and CTO | FTBL, and former analyst at Arsenal, Friday’s panel on football analysis.
3. We seek opportunities for women’s sports analysis.
Did you mention that women’s sports are booming? The WNBA is expanding, with the US relocation market for women’s soccer doubled for the third year in a row, with women’s college volleyball available to find basic cable packages.
That growth is beginning to fund larger data collection, including the WNBA, a frequently talked topic at SSAC.
Jennifer Rizzotti, president of the WNBA Connecticut Sun, focuses on her own play day in the 1990s. So, considering what players have access to now and how far we have come, it’s really impressive. “Even so, she still has a lot of data on men’s basketball ahead of women’s games.
Some women’s sports still lack the cash needed for basic analytical infrastructure. One Friday panelist, LPGA golfer Staysse, has won the tour 13 times, but said the popular ball tracking analysis system used in men’s golf costs $1 million a week, exceeding the budget for women’s games.
And on Saturday’s panel, Germain said the full data parity for male and female sports is not imminent. “The sad thing is, we need to invest more in it, so I think we’re apart for years,” she said.
But there is movement. In a talk on Saturday, data developer Charlotte Eisenberg detailed how the website’s sports references (an important resource for free public data) add per-play data to WNBA games. It helped to evaluate individual players, especially over a long period of time, and has been available for a long time in NBA games.
In short, as women’s sports grow, so do analytical opportunities.
4. Don’t be careful of someone’s blurred “eye tests.”
Even in SSAC, the subtle tripwire of sports analysis is the idea that the analysis must match the so-called “eye test,” or seemingly intuitive sports observations.
The problem is: There is no “eye test” in any sport because people have different intuitions. For some basketball coaches, selfish role players stand out. For others, even without a flashy shooting percentage, a flashy offdribble shooter passes the eye test. Even if statistics aren’t, that tension exists.
Enter an analysis to ensure that efficient shooting is highly valuable (and old-school virtues such as defense, rebound, and avoiding turnover). But with a twist, the definition of a good shot in basketball has changed to famous. From 1979 to 1980, the NBA introduced a three-point line. In 1985, the team had 3.1 pointers per game. Currently, between 2024 and 25, the team averages 37.5 3 pointers per game, making it extremely efficient. what happened?
“People didn’t use (three-point shots) well at first,” Molly said on Saturday’s panel.
Certainly, players were not used to filming Three in 1980. However, it took a long time to change the intuition of sports. Today, the analysis shows that the contested three-pointer is a valuable shot of opening an 18-foot two-pointer. It could still counter someone’s “eye test.”
Incidentally, following analytically informed coaching at all times can lead to a more standardized, less interesting game, as Molly and basketball legend Sue Bird proposed on the same panel.
“There’s a bit of instinct that’s now been removed from the game,” Bird said. Shooting Three makes sense, but she agrees, “You’re focused only on the three-point line and you’re taking everything else.”
5. Think about the absolute truth. But solve your current tactics.
Bill James set the bar high for sports analysis: his groundbreaking equation, “Runs Created,” explained how baseball works with almost Newton’s simplicity. Team runs are the product of base percentage divided by plate appearance and slugging rate. This applies to individual players as well.
However, it is almost impossible to replicate such basic formulas in other sports.
“In football, I think there’s still tons to learn about how the game works,” Ohanlon told MIT News. Should teams patiently build their possessions, play long balls, or push them high? And how do you rate players with very different roles?
This leads to situations where Ohanlon points out, “No one really knows the right questions that the data should be asking for because they really don’t know the right way to play soccer.”
Luckily, the search for fundamental truth can also generate some tactical insights. Consider “the machine learning approach to player values and decision-making in the ultimate professional Frisbee” by Braden Eberhard, Jacob Miller and Nathan Sandholtz, one of the three finalists of the conference’s research paper competition.
In it, the author examines the ultimate play pattern and see if the team scored more scores by using a longer percentage of higher range short-range passes or trying longer risk throws. They found that there are several variations among star players, but players tend to try a higher percentage of passes. It suggests a tactical flexibility issue. If the defense is trying to take a short pass, it sometimes throws longer.
It’s a classic sport problem. Often, the correct way to play depends on how your opponent is playing. In search of the ultimate truth, analysts can reveal the usefulness of short-term tactics. This will help your team win. This helps to maintain the adoption of the analytic type. However, this will not be revealed if analysts are not digging into the sport they love, looking for answers and trying to let the world know what they have found.
“Nothing happens here that will change your life unless you follow it,” James said. “But there is a lot going on here.
