LeBron James: 'I Don't Even Know What the Hell Analytics Means'

Andrew HanFeatured ColumnistOctober 15, 2013

MIAMI, FL - JUNE 20: LeBron James #6 of the Miami Heat waits to be interviewed while sitting with the Bill Russell NBA Finals Most Valuable Player (MVP) trophy following the Heat's victory against the San Antonio Spurs in Game Seven of the 2013 NBA Finals on June 20, 2013 at American Airlines Arena in Miami, Florida. NOTE TO USER: User expressly acknowledges and agrees that, by downloading and or using this photograph, User is consenting to the terms and conditions of the Getty Images License Agreement. Mandatory Copyright Notice: Copyright 2013 NBAE (Photo by Jesse D. Garrabrant/NBAE via Getty Images)
Jesse D. Garrabrant/Getty Images

It was just another mundane preseason shootaround for the Miami Heat. Coaches were focused on making sure all their sets were installed, possibly evaluating the last remaining training camp invitees for an end-of-the-bench roster spot. Players were concerned with making sure their skills and conditioning were optimally tuned and they were in sync with their teammates.

And then this quixotic nugget found its way out into the world, per Shandel Richardson of the South Florida Sun Sentinel

LeBron on analytical basketball: "I don’t even know what the hell analytics means." He then told us that's a question for Shane Battier.

— Shandel Richardson (@ShandelRich) October 15, 2013 

This would be alarming, to say the least, if it were true. And that's not to say there aren't analytics skeptics in the league. In fact, you could claim that the majority of the indoctrinated decision-makers in the NBA at a minimum hold analytics at arms reach. Take, for example, former Memphis Grizzlies coach Lionel Hollins in a radio interview with Memphis' Sports 56 WHBQ, as transcribed by SB Nation's Steve von Horn:

Analytics has a place. It can't be the be all end all. I'm still trying to figure out when the Oakland Athletics won a championship with all the analytics they have. It takes talent. We had a guy a few years ago that was sending me emails about different lineup combinations, and he was saying, "this lineup should be on the court a lot more because they're the most effective." So, then you coach that lineup and keep them on the floor for 40 minutes. I'm going to stay with the lineups that I have on the floor. No matter what anyone wants to say, there are players that get it done in the last six minutes, they're players that do it in the first quarter. When it comes down to big shots, there's only a few guys that will take those shots, want to take those shots, have the bravery and courage to take them. Because there's a lot of criticism when you miss a shot. You have to be mentally tough and courageous to take those shots at the end of the game.

As much as statheads, analysts and the blogosphere champion analytics and advanced statistics, Hollins' sentiments probably fall more in line with the majority of fans, players and teams. But really, there are so many useful elements to analytics without even getting into linear regression, projection modeling and advanced math and programming.

More than anything, analytics is a tool that helps provide better context for things that are not easily explainable, like these common terms, for instance:

PACE: Teams play at different speeds from others, creating misleading raw numbers. If Team A shoots 50 percent more than Team B but only scores 10 percent more points, it may seem like Team A is better based on points, but clearly, it is less efficient. Pace informs how many possessions a team uses per game.

Offensive Efficiency (a.k.a. Offensive Rating): A formula that neutralizes PACE in number of points scored. The offensive efficiency number reveals how many points a team would score per 100 possessions.

Defensive Efficiency (a.k.a. Defensive Rating): A formula that neutralizes PACE in number of points allowed. The defensive efficiency number reveals how many points a team allows per 100 possessions.

Shot Charts: To some degree, this has long been used by players and coaches in film study. Being aware of what areas a player shoots more proficiently from and where he prefers to shoot the most is crucial in any game plan.

This is not some groundbreaking science or scratching at some hidden truth about basketball; it's merely revealing the evidence we intuitively understand to be true but don't recognize in the moment of action.

Don't confuse LeBron's comments as just another part-and-parcel remark in the disdain for analytics, however. Not only does he hold his analytics-friendly teammate, Shane Battier, in high regard, but he's also already revealed himself to pay close attention to the cerebral aspects of the game. This from his interview following Game 7 of the 2013 NBA Finals, per NBA.com/Stats:

I watched film, and my mind started to work and I said, "okay, this is how they're going to play me for the whole series." I looked at all my regular-season stats, all my playoff stats, and I was one of the best mid-range shooters in the game. I shot a career high from the 3-point line.

I just told myself "don't abandon what you've done all year. Don't abandon now because they're going under [screens]. Don't force the paint. If it's there, take it. If not, take the jumper."

Like Keyser Soze in The Usual Suspects, LeBron is cheekily shrugging his shoulders and feigning ignorance, all the while consuming every bit of basketball data to give him every bit of advantage there is. And that's analytics: mining data.