The NBA’s obsession with analytics isn’t ending anytime soon. But despite teams across the league leaning harder than ever into advanced statistics, many players are wary of the impact they’re making on the game.
Kevin Durant is among the countless players who have expressed distaste with the league’s increasing reliance on analytics. The Brooklyn Nets superstar provided fans with an unfiltered view of his issues with basketball’s ongoing statistical revolution, engaging in a lengthy tweetstorm with Matt Moore, NBA writer for The Action Network. The Twitter thread both explains the pitfalls of Durant’s thinking and makes it much easier to understand where he and other players are coming from.
The conversation was sparked by recent comments from Chicago Bulls star Zach LaVine in which he lamented his team prioritizing three-point attempts and shots at the rim ahead of two-point jumpers. LaVine, echoing a tired trope, called the mid-range game a “lost art,” insisting that a team putting the ball in the hands of its best player and letting him create “the shot he needs” is sometimes an offense’s best means of attack. Durant responded with “Shoot em Zach,” an endorsement of LaVine’s proclivity for off-dribble twos, the most inefficient shot in basketball.
During his subsequent discussion with Moore, Durant made the point a lot of scorers do when pressed for their thoughts on analytics: long twos aren’t inefficient by nature but because players no longer practice them.
That’s an assumption usually made by those who doubt what others believe are the positive, all-encompassing effects of the analytics movement. But accuracy on mid-range shots has stayed mostly static dating back 20 years, when those attempts were taken more than twice as frequently as they are today.
Durant is an outlier in every sense of the word. At nearly seven-feet tall with a deft handle, he’s one of the best shooters in the world wherever he is on the court. He connected on 55.1 percent of his mid-range jumpers last season, leading the NBA by a wide margin. It’s almost impossible for Durant to take a “bad” shot – he’s just that good.
Not every player is a four-time scoring champion and two-time Finals MVP, though. Defending his skepticism about fully embracing analytics, Durant suggested shooters who are below league average from beyond the arc should swap threes for long twos.
The problem with Durant’s logic? Even a subpar 33 percent three-point shooter yields more expected points per attempt (.99 points) than a solid 40 percent shooter from mid-range (.80 points).
Just like players aren’t created equal, neither are the quality of field goal attempts.
The most common critique of advanced statistics is that they fail to account for “feel.” Focusing too much on expected shot value could easily lead to diminishing returns, sapping the best players in the world of real-time creative freedom.
That’s why Durant doesn’t “view the game as math.” Doing so wouldn’t just subtract from the joy and flair that propelled him to NBA superstardom but more importantly make him easier to defend.
It’s different for role players, though.
Stars at or approaching Durant’s place on the individual hierarchy can get away with largely ignoring the numbers. But for ancillary offensive pieces, concentrating on spot-up three-point shooting and cuts to the rim are their surest means of both producing points and affording star teammates necessary space to operate all over the floor.
There’s room in the middle of the advanced statistics debate, and it’s where most smart basketball minds settle even if they get there from opposite ends of the spectrum. Implementing analytics into team strategy is a prerequisite for success in the modern NBA, but doing so at the expense of open shots – especially in the playoffs when high-value attempts are much harder to generate – sets an offense up to fail.
Durant, somewhat reluctantly, ultimately seemed to acknowledged as much, too.
This article was edited by Gerelyn Terzo.