I'm considering writing my second paper on how analytics has changed the style of play in the NBA and how it has broadened the sport's appeal amongst those who wouldn't normally be considered the typical sports fan. I'm compiling various sources and thoughts here.

Long 2s

https://www.nytimes.com/2019/11/27/sports/basketball/nba-analytics.html

Shot selection

Players appear more skeptical of analytics despite the fact that it has radically changed the way they play the game. No one is more opposed to the analytics revolution than Kevin Durant, one of the greatest players of the past decade.

What are the shortcomings of the current data-driven approach? What factors does it fail to capture that contribute to NBA success? (e.g. heart/grit/work ethic/ "believing in yourself")

Will we reach a point were every optimal basketball decision can be calculated? Measure what is measurable, make measurable what is not so.

Charles Barkley on proponents of analytics "They're a bunch of guys who ain't never played the game, and they never got the girls in high school, and they just want to get in the game."

Is Basketball an Art or a Science? (It's both)

Introduction

The Houston Rockets are playing the Memphis Grizzlies in a Western Conference matchup. Carmelo Anthony, the Rocket's power forward, receives the ball just outside the three point line on the left wing. He feints a shot, causing his defender to catapult into the air in an attempt to block a three-point attempt that doesn't come. While his defender flails in midair, Anthony takes one dribble inside the three point line, raises up for an uncontested shot, and drains it. Two points for the Rockets. As Anthony jogs back to the defensive end, he smiles, looks over to the Rocket's coaching staff, and mouths, "my bad." Why the need for an apology? Anthony stymied his defender and put two points on the board. The reason: you don't take long twos. For the Houston Rockets, the only acceptable shots are either three-pointers or a layups, everything else is analytically unsound

The next day, sports talking heads discussed the seemingly inconsequential play ad nauseam. The Old Guard pounded the table and mourned the death of the "midrange shot." They defended Anthony's play and dismissed NBA analytics as a fad that has no correlation to team success. Charles Barkley, an NBA hall of famer and analyst on the emmy-awarding winning Inside the NBA, decried analytics and characterized its proponents as "a bunch of guys who ain't never played the game, and they never got the girls in high school, and they just want to get in the game." Despite these criticisms, it seems as if analytics is here to stay.

Definition of terms

Why are Players Arguably the Biggest Opponents of Analytics?

The Shortcomings of an Analytically Driven Approach

Many fans don't flip on basketball games to listen to analysts breakdown statistical probabilities. They want to see ginormous humans accomplish seemingly impossible feats of athleticism with apparent ease. A fan doesn't cheer after seeing a dunk because it was a "high percentage shot." They cheer because a 7 foot tall man just jumped three feet into the air and slammed a basketball into the hoop with enough force to snap my mortal frame in half.

The midrange shot is only dead for role players. Stars still thrive in these areas because they are so skilled as to make the shot valuable.

Analytics does not capture many of the off-court intangibles that contribute to team success. Team chemistry, work ethic, etc. do not currently have a

The Future of NBA Analytics (Measure what is measurable, make measurable what is not so)

"Killer instinct" has become measurable via the clutch points statistics. Is this an imperfect proxy? Will we eventually be able to measure chemistry, work ethic, heart? Would the result of such comprehensive measurement act as a double slit experiment? Observer effect