July 25, 2015


Before Beane : The origin story of AVM Systems, the little-known company that jump-started sabermetrics and made Moneyball possible (BEN LINDBERGH,  JULY 24, 2015, gRANTLAND)

Somewhere in your favorite sports franchise's front office, a team of analysts is teasing the truth out of a mess of misleading statistics. Regardless of the sport or the data source -- Corsi, SportVU, or Statcast -- the analysts' goals are the same: to capture contributions that standard statistics omit or misrepresent, and to find the positive indicators buried beneath superficial failures. The shot on goal that goes wide? In a sense, it's a good sign, since it might mean more shots in the future, some of which will find the net. The line drive caught by a leaping outfielder playing out of position? A double would've been better, but even an almost-double tells us that the player who came close to extra bases has the skills to drive the baseball at a speed and trajectory that would typically lead to a hit. Not all outs are created equal.

Whether they know it or not -- and nowadays, most of them don't -- all of these quants are re-proving the principle at the core of a product developed two decades ago by a company called AVM Systems, a small outfit founded by Ken Mauriello and Jack Armbruster, two businessmen based in the Chicago suburb of Wheaton, Illinois. AVM's central insight sounds hackneyed now, but it was -- to borrow a latter-day business buzzword -- disruptive at the time: Process is important, because results are sometimes deceiving. [...]

You might remember AVM (Advanced Value Matrix) from its cameo in Moneyball­ as the purveyors of then-Oakland assistant GM Paul DePodesta's secret weapon, a system that helped the A's determine (among other things) that the difference in defense between center fielders Terrence Long and Johnny Damon wasn't large enough to justify the difference in salary. AVM did this, Michael Lewis wrote, by "collecting ten years of data from major league baseball games, of every ball that was put into play," and then comparing the outcome of each individual play to the average outcome of all plays with similar characteristics.

Consider the case of a home run robbery, in which an outfielder perfectly times a jump and pulls back a ball from beyond the wall. Traditional stats would credit the outfielder with a putout, the pitcher with a batter retired, and the batter with an out made, making no distinction between the near-dinger and a lazy fly ball, even though the two types of plays tell us dramatically different things about the abilities of the players involved. AVM would chalk up most of a homer to the hitter, crediting the fielder and docking the pitcher by similar amounts. Home run robberies are rare, but by following a similar process for every play, AVM could arrive at a more complete accounting of players' contributions on both sides of the ball.

As one would expect, the value of this exercise wasn't always an easy sell to prospective clients. This was several years before the publication of the Baseball Prospectus study that eventually led to BABIP becoming a common fantasy tool, and the idea that luck made a meaningful difference in a player's performance over the course of a 162-game season met with some resistance.

"They'd always say, 'Well, it comes out in a wash,'" Armbruster says. "The hard liner that's caught, but then a soft hit. We were showing them it usually does, but it doesn't always come out in a wash. There's always going to be that one player out of 20 who's going to be pretty far off from what the numbers are showing. And there's going to be one guy in the league who's just off the charts. You need mathematics to understand that. To understand that if you flip a coin 20 times, it could come up heads 16 times. It doesn't mean it's a very talented coin. It's the randomness of life."

Posted by at July 25, 2015 10:16 AM

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