In 2026, analytics in basketball are being used at an all-time high. And yet, it's possible that our general understanding of analytics in basketball is falling to a new low.
In a way, I can understand where the disconnect is coming from. The NBA's high-profile analytics debate has been dominating online news cycles recently, from the controversial trade of Jaylen Brown, to Cleveland Cavaliers coach Kenny Atkinson saying his team was "analytically" winning a series against the New York Knicks that they were eventually swept.
Retired NBA players are fighting with social media accounts about the use of numbers in basketball, and it seems like the term "analytics" is used more as a weapon in a hoops argument than a tool.
In college basketball, this debate is not as fierce, but the divide exists in the same way. There are firm analytics believers to a fault, and there are stubborn analytics deniers to an equal fault.
However, when I decided to do a primer surrounding analytics in college basketball following my frustrations with online discourse over the last couple of months, it wasn't because I wanted to indoctrinate non-analytics believers with the power of numbers in basketball.
Rather, all the discussion on the topic made me realize that there remains a critical lack of understanding of what analytics in college hoops actually represents and how it's used.
To help convey the real ways analytics are shaping the game, I reached out to a handful of team representatives who have worked in college hoops across a wide variety of roles. They each shared valuable insights into what analytics means to them personally and in their day-to-day work, helping define what the concept actually means.
