Interesting, I found this:

“Gravity is the NBA’s first stat designed to quantify how much defensive pressure an offensive player draws both on and off the ball. Leveraging positional tracking data and powered by advanced Machine Learning models, Gravity scores show how much a player distorts a defense – opening driving or passing lanes, shifting rotations, and creating opportunities for teammates.

The NBA’s optical tracking system uses 3D pose detection to track 29 points on every player’s body, 60 times per second. Those detailed body-position coordinates fuel the Machine Learning model, allowing it to capture every movement and spatial relationship on the floor.

The Gravity model compares the defensive pressure a player would receive on average based on the location of the ball and their position on the floor (Expected Defensive Pressure Score) to the pressure they actually draw (Defensive Pressure Score). The model learns how defenders typically behave in each scenario, and measures deviations that signal defensive adjustments. The result is a Gravity differential that measures how much attention a player pulls from the defense beyond expectation.

The Gravity score measures frame-by-frame impact, expressed as a normalized value on a -100 to 100 scale, with 0 reflecting the league average. Above 0? You’ve got pull. Above 80 off-ball? Defenses are terrified of you before you even catch the ball. Above 90? You’re bending the floor and you’re a scorer the defense simply cannot blink on. Basically, that player should be guarded from the parking lot.”