ESPN Story: Barkley Rips Rockets GM, Use of Stats

March 9, 2016 by Matt McCracken

I am sure Charles Barkley has a bunch of detractors – but the guy is funny.  And entertaining.  If I ever watched NBA basketball, I’d be sure to take in his commentary.

ESPN reported a story last night about how Barkley denounced the use of stats in sports calling out the GM of one of his former teams.  My favorite quote from the article is when Sir Charles said regarding the stats guys is, “its proponents were ‘a bunch of guys who have never played the game, and they never got the girls in high school.’”.  Well in response to Sir Charles, I use stats, I played the game at the NCAA level and I certainly got a girl or two in HS.  But that is not the point of this commentary.

Charles goes on to say that the use of stats is not only useless in the NBA, which I agree with, but that they are also useless in baseball.  My first question for Charles would be, “when did you play baseball? Because I’ve caught a glimpse of that golf swing of yours and it is painfully obvious, you can’t swing at anything and hit it.” 

When it comes to baseball and stats, I take issue with Chuck’s opinion.  First, he states that no team has won using stats.  Which is blatantly wrong.  The Red Sox used stats and won the series - twice.  They tried hiring Billy Beane away from the A’s with gobs of money that would normally be reserved for a “shut-down, south-paw flamethrower”.  When Beane turned them down, they hired Theo Epstein which bought into the same analytics approach.

The key difference between baseball and basketball is that baseball is a mono y mono sport with the pitcher being pitted against a hitter.  Every pitcher basically faces every hitter.  With a large enough sample size, it is easy to determine who are the best hitters and who are the best pitchers.  In basketball, defense is a key as Charles points out – defense that is practically impossible to measure.  Additionally, a team’s best defender may be put on another team’s best offensive player therefore skewing the stats. 

Years ago, I knew a scout for an NBA team and he would say over and over again, “on every NBA team, someone is going to drop 20 points a game.”  But the guy who scores 20+ nightly for the 76ers may be the 4th guy off the bench for the San Antonio Spurs.  A .300 hitter for Astros is probably just as good as a .300 hitter for Giants.  But a 20+ point guy for the 76ers ain’t as good as a 20+ point guy for the Spurs.    

But here is the real rub – The Oakland A’s under Billy Beane used analytics not as an end in and of itself but rather as a means to an end.  Stats were a means of finding undervalued talent.  Period.  And when everyone starts using the same stats, they no longer identify undervalued talent because everyone is using the same valuation metrics.   Analytics only works if no one else is using it.  Any method of valuing something can only work when its use is limited.   

What I find fascinating is that in the book Moneyball, high school and unproven college pitchers were identified as the most overvalued asset in the MLB draft.  And once the book shined a light on the foolish idea of spending early picks on unproven pitchers, their draft stock dropped.  It was no longer popular to “aim for the bleachers” with a pitcher. 

So what happened?  pitchers went from being overvalued to undervalued.  And how  did Bean respond?  In the 2007 draft at the height of the Sabermetrics debate, Beane used 8 of his first 13 picks on pitchers –  in exact contradiction to what Moneyball advised against.  And he did not do it because the stats agreed with it but because Beane understood they had become undervalued.  And ironically, they became undervalued because of the book that told his story said they were overvalued.  You might say Beane unintentionally talked up his own book.