05.26.14 9:45 AM ET
The Nate Silver of Sports Injuries
Jeff Stotts is no Memphis Grizzly but last November 22 he got an assist from Marc Gasol all the same. That night Gasol hobbled off his home court with a torn medial collateral ligament in his left knee. Nobody knew when the Grizzlies’ star center would return, but Stotts had a better idea than many. The statistically inclined athletic trainer hopped on his Mac to pull numbers from a database he’d created for fun. They showed in recent years eight other players had suffered Gasol’s type of MCL tear; on average, players with torn MCLs miss 23 games.
Stotts’ resulting Tweet went viral. Hundreds of thousands of people crave this kind of info not because they innately care for Gasol, but because they have money on the line in their fantasy basketball league. “It’s a billion-dollar industry,” Stotts said. “You want to have the right people in at the right time.” This demand has allowed Stotts to carve out a niche in the last six years as possibly the nation’s top injury analyst for fantasy basketball, baseball, and football.
Yet Stotts wanted wider reach by crossing over into real sports, so he started tracking injuries in his favorite sport, the NBA, and launched a Web site to showcase his data. This info is increasingly valuable to not only news outlets—ESPN’s FiveThirtyEight hit him up for a comparison across all four major sports leagues in the wake of Paul George’s Tuesday night concussion—but potentially to NBA teams and players as well. A Phoenix Suns-affiliated physical therapist and doctor have contacted him to swap info and ideas, Stotts said.
Stotts got even more credibility when Gasol came back from his MCL tear after exactly 23 games. This was latest sign of Stotts’s prescience. The 31-year-old Dallas native, after all, chose a hobby in injury analytics that just happens to be the next big thing in sports. “Injury is kind of the golden question that everybody wants to answer,” sports scientist Michael Regan told ESPN’s TrueHoop. “Because when you look at analytics in sports, the only thing that correlates consistently with elite performance and championships, is number of games played by your best players.”
Stotts calls his year-and-a-half-old database a “random, crazy idea,” but its premise is simple and straightforward. Each game night during the NBA season—often after watching some Mavericks basketball with his 3-year-old daughter and tucking her into bed—he fires up Excel. He then notes which players that night suffered an injury (or were kept out because of an injury) and what the injury was. Sources include news articles and databases and archives available through Rotowire, the fantasy sports company for which he writes. So far, he’s tracked the entire injury histories of 866 players dating back to the 1984-85 season.
The key, as any advanced statistician worth his spreadsheet knows, is to look beyond the box score. The official game report may list the reason a player was kept out as “Did Not Play—Coach’s Decision” but Stotts knows there’s often more to the story. After a little patience and some Googling, he’ll usually discover in news accounts a minor injury like a sore hamstring was the real culprit. “Well, it should have been noted as sore hamstring, but in the box score all it says is ‘DNP-CD.’”
Stotts attention to detail helped spark a friendship with national sportswriter Will Carroll, a Bleacher Report columnist who specializes in baseball injury reporting. The two writers have teamed to present an annual award for the best medical staff in Major League Baseball. Stotts said he also hopes to launch similar awards for NFL and NBA medical staffs, with his database helping decide the latter. Before getting to that point, though, he’ll need more data to track year-to-year improvement trends. “You don’t want to reward a staff for getting lucky. You want to make sure this is a little bit of a trend.”
To that end, Stotts plans to keep working on his database, hopefully adding three seasons’ worth of player histories this summer. The time won’t be as intense as it is on the busiest game days of the regular season— when his news scouring and recording takes about an hour per night—but it’s still an investment for a busy family man with a day job as an athletic trainer at a Catholic high school in Little Rock, Arkansas. He tries to work on his hobby when nobody’s home, but that’s not always possible. Occasionally, his wife Emily will tell him “Are you really seriously getting on that computer again?” he said, chuckling.
“She’s been extremely patient with me. Very supportive,” he added. “She understands there’s a method to my madness, that hopefully it will pay off somewhere down the road.”
How that will happen isn’t yet clear, although there have been inquiries. “I’ve been contacted by a couple of people looking to buy or seek to get access to part of the data, which I’m obviously very hesitant to do because there’s been a lot of labor into it,” he said. It’s “kind of my baby.”
Down the line, he’d love to craft injury-prevention strategies with NBA general managers or directly with players. But, for now, “I do it because I love it.” He’s also excited by the challenge of acquiring the ability to predict the likelihood a specific player will suffer an injury in a specific game. This is a field which is becoming one of the most lucrative in injury analytics, and Stotts’s data would be just a piece of the medical picture team physicians could piece together when forming predictive models for the players. Already, a Major League Soccer team has developed a model “with a really solid accuracy for injury prevention,” Regan said. For a whole season, that team ran the model in the background. “What they were able to see is that when they predicted a 30 percent chance of injury, there was actually a 33 percent chance of injury incidence if they didn’t intervene.”
Such predictive power would be especially useful for the Indiana Pacers, who had to weigh the risks involved in playing superstar Paul George as they prepared for Game 3 with Miami on Saturday night. Was it worth incurring the potentially devastating consequences of two concussions suffered within four nights for the increased chance of knocking off LeBron James and the Heat?
Producing a statistically informed answer to that question will take a long while. Given the myriad of variables at play, a predictive model for concussion injury risk seems more fantasy than reality at this point.
With analysts like Jeff Stotts rising on the scene, though, a crossover may happen sooner than you think.