How metrics saved Dragic's value

To kick off the ninth annual MIT Sloan Sports Analytics Conference, held Friday and Saturday in Boston, the marquee opening panel highlighted retired NBA veteran Shane Battier (now an analyst for ESPN) and revisited a long-form feature on Battier penned by "Moneyball" author Michael Lewis for the New York Times in 2009.

There's a telling line in Lewis' article. Houston Rockets owner Leslie Alexander admits he was reluctant when GM Daryl Morey -- the co-founder of the Sloan Conference -- first brought up the idea of trading the eighth pick in the 2006 draft (used on Sacramento Kings forward Rudy Gay) to the Memphis Grizzlies for Battier. "All I knew was Shane's stats, and obviously they weren't great," Alexander said. "[Morey] had to sell me. It was hard for me to see it."

Depending on the way the term is used, Battier can either be "The No-Stats All-Star" (the title of Lewis' piece) or the ultimate example of the value of statistical analysis. That reveals a pair of important points. First, even the most ardent opponents of statistical analysis are still using stats to draw conclusions. And second, the type of stats we use matter when it comes to valuing players. This was especially important in regards to Miami point guard Goran Dragic and how he was viewed at the trade deadline.

Not using stats, using the right stats

In a certain sense, the notion of an analytics revolution in basketball is preposterous. This isn't soccer, a sport that traditionally has had few measurable statistics. Since the NBA started tracking player turnovers in 1977-78, the format of the box score hasn't really changed. Per-game stats and field goal percentages have been tracked for decades and decades, becoming an integral part of the way we talk about and understand the game.