Data Science and the 3-Point Revolution in the NBA

By Abraham Gibson

In the history of sports lore, there are a handful of “revolutions” that every fan should know. There is the “Fosbury flop,” which American high-jumper Dick Fosbury introduced to the world at the 1968 Olympic games in Mexico City. While his competitors jumped over the bar leg-first, Fosbury jumped back-first, better utilizing his body’s angular momentum. He won gold, and within a few short years, every high jumper in the world had adopted his style. American football experienced a similar revolution around the exact same time. While place-kickers had long kicked the football straight on, with their toe, Hungarian place-kicker Pete Gogolax introduced a side-on, “soccer-style” kick that better utilized angular momentum and thus yielded longer field goals.

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Dick Fosbury revolutionized the sport of high jumping when he debuted the “Fosbury flop” at the 1968 Olympics in Mexico City. Dan Reilly, “100 Greatest U.S. Olympians,” Rolling Stone, February 7, 2014

The sports world is currently witnessing an even bigger revolution, but of an entirely different sort. This time around, the label is most often applied to the rise of data analysis, or “analytics,” for short. Most date the origin of the revolution to American statistician Bill James, who began publishing a series of now-classic books and articles on the empirical analysis of baseball statistics (known as “Sabermetrics”) in the 1970s. Despite his celebrity among stat geeks, however, James had still not influenced the American sporting landscape in any discernible way as recently as the 1990s.

That famously changed in 2002, when Oakland Athletics general manager Billy Beane built the team’s entire roster using data-driven “moneyball.” Beane’s efforts, later dramatized in an award-winning book and a surprisingly moving film starring Brad Pitt, helped spark a new era in professional sports. Embracing analytics helped the Boston Red Sox snap the 86-year “Curse of the Bambino” in 2004, and other teams have been quick to follow suit. The MIT Sloan School of Management hosted the first Sports Analytics Conference in 2007, and the event has grown in scale and influence ever since. ESPN: The Magazine published its inaugural Great Analytics Rankings in 2015, and news outlets like the New York Times, Forbes, and 60 Minutes have all ran lengthy features on the “analytics revolution.”

No other league has embraced analytics like the NBA. In fact, analytics have triggered a radical transformation within the game: the 3-point revolution. The NBA first adopted the 3-point line as something of a gimmick in 1979, but gameplay was scarcely affected. Teams attempted just 2.8 threes per game during that first season, and the 3-pointer remained an ancillary tactic for decades thereafter. Things began to change with the rise of big data. Statistical analyses suggested that shooting a lot of threes could actually optimize scoring efficiency, if one could find a sufficiently gifted shooter.

 

All of which brings us to Steph Curry, the lanky sharpshooter with lethal range. Curry is blessed with a kind of idiosyncratic genius when it comes to shooting threes. In 2012, coaches and management instructed him to shoot threes far more frequently, and that is when his anomalous talent was truly revealed. Most players grow less efficient the more they shoot, but Curry was just the opposite. He remained so efficient for so long that, from an analytics perspective, the Warriors should ask Curry to shoot the ball as much as possible. That same year, Curry broke the record for threes made in a season (272). He broke his own record each of the next three seasons, making an astounding 402 threes during the 2015-2016 campaign. His unprecedented performances earned him two straight MVPs, and he utterly transformed how the game is played. As Benjamin Morris of FiveThirtyEight once wrote: “Steph Curry is the revolution.”

He is certainly at the vanguard, but he is no longer the only revolutionary in the game.  Over the past several years, several different teams have staked their entire future on analytics. This can manifest in different ways, from player evaluation to usage rates, but it usually means shooting a lot more threes. As recently as 1998, during Michael Jordan’s last season with the Chicago Bulls, NBA teams attempted just 12.7 threes per game. This season, teams are attempting over 31.3 per game. Numerous media outlets, including The Atlantic, the New Yorker, and the Wall Street Journal, have heralded the “analytics revolution” and the “3-point revolution” as the dawn of a new age in basketball.

No team is more closely associated with data-driven basketball than the Houston Rockets, who are currently shooting 44.8 threes per game. The team’s general manager, Daryl Morey, helped establish the MIT Sloan Sports Analytics Conference, and he is now the league’s foremost advocate for data analysis. That devotion has left the Rockets with one of the strangest offenses in the league. Ever since the team’s second-best player, Chris Paul, was injured a few months ago, the Rockets have relied almost exclusively on their best player, James Harden, whose style of play is polarizing. Consider that more than two-thirds (66.9%) of Curry’s threes are assisted, meaning he catches a pass from a teammate before shooting, whereas scarcely 13.2% of Harden’s threes are assisted. And then there’s Harden’s knack for getting fouled. Whereas Curry attempts just 4.7 free throws per game, Harden attempts 11.4 per game. One style of play is far more aesthetically pleasing than the other, but that does not necessarily make it more effective. To wit, Harden currently leads the league in points per game, 3-pointers attempted, and 3-pointers made.

Harden.jpg
Launched by award-winning illustrator Filip Peraić in 2013, James Harden Illustrated is an art project that depicts James Harden in profile using a variety of media, techniques, and styles.  
Filip Peraić, “Psychedelic James Harden” (2014).  

Many fans and former players reject the validity of analytics altogether. Last year, the inimitable Charles Barkley, co-host of NBA on TNT, denounced Morey and other “idiots who believe in analytics” and proclaimed that “analytics is crap.” Michael Wilbon, co-host of ESPN’s Pardon the Interruption, wrote a more eloquent but no less emphatic rejection of analytics in a column for The Undefeated a few years earlier. It’s hard not to feel bad for Harden, who is playing the best basketball of his career, while also bearing the brunt of anti-analytics vitriol. One can detect a hint of genuine remorse when he tells reporters that he’d prefer not to play “hero ball,” and that he too would prefer a more team-oriented style of play. Even those who believe in the power of analytics disagree on its implications. Some insist that data science will take basketball to soaring new heights of athletic artistry—that it will produce dynamic styles of play we have not yet even considered. Others insist that analytics will sap the joy from sports, and that its emphasis on machinelike efficiency will render basketball more calculating and less creative.

There is no guarantee that readers of Age of Revolutions will be fans of basketball, but I encourage you to occasionally check in with the NBA over the next several months as the regular season winds down and the playoffs wind up. It’s not often one can watch a revolution with (relatively) low stakes unfold on a nightly basis. The results may well prove instructive. Professional sports may strike some as frivolous, but they often serve as a bellwether for emergent trends in society. Experts assure us that data science is destined to transform every aspect of our lives, but it’s not clear what that means or what it will look like. Basketball may offer a clue. A revolution hangs in the balance.


Abraham Gibson (@AbrahamHGibson) is a Postdoctoral Fellow in the Center for Biology and Society at Arizona State University. He has published extensively on a variety of topics in the history of science, technology, and engineering. His current research looks at the social and cultural influence of data science.

Title image: This visualization charts every 3-pointer that Steph Curry has made since joining the NBA. Kirk Goldsberry, “Steph Curry is Still Completely Unfair,” ESPN.com, January 16, 2019.

Further Reading:

Benjamin Baumer and Andrew Zimbalist, The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball (Philadelphia: University of Pennsylvania Press, 2014)

Kirk Goldsberry, Sprawlball: A Visual Tour of the New Era of the NBA (Houghton Mifflin Harcourt, 2019)

“Great Analytics Rankings,” ESPN: The Magazine (February 2015).

Michael Lewis, Moneyball: The Art of Winning an Unfair Game (New York: Norton and Company, 2004).

C.J. Moore, “The 3-point Revolution Has Taken Over College Basketball Too,” Bleacher Report, March 2, 2018.

Benjamin Morris, “Steph Curry is the Revolution,” FiveThirtyEight, December 3, 2015.

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