When Ty Lawson declared for the NBA draft in 2009, he was one of the best players in college basketball. He had just led the North Carolina Tar Heels to a national championship, earning player-of-the-year honors and an award given to the top college point guard.
The problem was, listed at 5’11”, Lawson didn’t have the size and stride of other guards. But that didn’t matter to Dean Oliver, head of the Denver Nuggets’ nascent analytics group—and a pioneer in the growing field of basketball analytics. Compared with what other successful NBA players had done in college, Lawson was just as good. He scored, racked up assists, took care of the ball, and was adept at picking up steals. Adding all that up, Oliver projected Lawson to be a top point guard and lobbied hard for the Nuggets to pick him.
The idea met with some resistance, but Oliver found support from Mark Warkentien, then the vice president of basketball operations of the Nuggets and the man who had hired him in 2006. Relying on conventional methods—using “eyes and ears,” as Warkentien calls it—Warkentien and some of the other scouts also thought Lawson was the best choice. Oliver’s analysis confirmed their instincts and helped to win over doubters. “The numbers screamed that Lawson was a great deal,” Warkentien says.
The Nuggets traded up to take Lawson with the 18th pick in the draft. He would turn out to be one of the best players taken that year and a solid floor general for years to come. “In hindsight, everyone thinks it was a steal,” says Warkentien, now the director of player personnel for the New York Knicks.
Oliver’s quantitative methods influenced nearly every aspect of the team: From line-up changes to game-day strategies, Oliver made a mark. “The next thing you know, we’re in the Western Conference Finals, [and] I get executive of the year,” Warkentien says of the Nuggets’ 2008–09 season, still the best in franchise history.
Oliver’s route to the NBA wasn’t conventional. First off, he studied engineering at Caltech. He played for the team, but even he admits he wasn’t very good. Because of a rare infection as a child, Oliver became blind in his left eye by the time he was 10. Although he didn’t have much playing time, he watched and learned about building offenses and defenses from then-coach Gene Victor. During Oliver’s junior and senior years, he traded his uniform for a clipboard and served as an assistant coach.
As an undergrad, Oliver already had an innate feel for statistics and thrived when he took quantum mechanics—inherently probabilistic and notoriously nonintuitive. “It was just more of the way my mind works,” he recalls. As exams were finishing up at the end of his freshman year, he kept close track of the NBA Finals, developing methods that would become the foundation for analytics today used in the industry.
Even when he went to grad school, basketball remained a passion. “I thought about basketball all the time,” he says. While Oliver studied environmental engineering at the University of North Carolina, Chapel Hill, he also worked as a scout for the perennial basketball powerhouse, scoping out teams like Duke and Wake Forest.
Oliver continued developing his own ideas for using statistics to understand and optimize basketball strategies and wrote a weekly web column while beginning his career as an environmental engineer. He quantified how being an efficient team comes down to shooting, turnovers, rebounding, and free throws. His analysis also demonstrated that the harder a player tries to score, the less efficient he is, as well as revealing that during the last few seconds of the shot clock, NBA offensive efficiency drops.
When he learned that famed baseball statistician Bill James wanted to write a basketball book—after asking Oliver to share some ideas—he realized he needed to do the same, lest he be scooped. So he took a leave from work and wrote Basketball on Paper, published in 2004 (a year after Michael Lewis’s bestselling Moneyball spotlighted analytics in baseball). As it turned out, James never wrote his book and instead endorsed Oliver’s.
“It’s a tremendously important book in terms of understanding a sport from a statistical point of view,” says Ben Alamar, director of production analytics at ESPN. “It’s the top book in the field for sure.”
Oliver ended up quitting his engineering job altogether and spent most of 2004 traveling around the country, talking to as many NBA insiders as possible. By October, he’d landed a job with the Seattle Supersonics.
What stood out for Warkentien, who hired him two years later for the Nuggets, was Oliver’s recognition that numbers were only part of the decision-making process and—perhaps more importantly—his ability to bridge the divide between stat geeks and old-school coaches. “You have to speak their language,” says Oliver. “You speak basketball to them.”
After his stint at Denver, Oliver helped lead ESPN’s analytics department, before heading off to the Sacramento Kings. While at ESPN, he developed tools like the college football and basketball power indices, which predict team successes, and a system called Total Quarterback Rating (QBR). Both are now essential parts of ESPN’s coverage.
Today nearly every NBA team has an analytics department. “People who are analysts now have jobs in the NBA because of Dean,” ESPN’s Alamar says. While not everyone’s convinced of the power of analytics (just ask Charles Barkley), attitudes have changed. After all, when millions of dollars are at stake, you want as much information as possible. “If you choose to absolutely ignore numbers,” Warkentien says, “then that’s just foolish.”
As for Ty Lawson, he was recently traded to the Houston Rockets, who reached the Western Conference Finals last year. The Rockets believe Lawson is the missing piece to a championship team. And because of basketball analytics, Oliver says, Houston knows what it’s doing.