Sep 27, 2013; Miami, FL, USA; Detroit Tigers president David Dombrowski addresses members of the media prior to a game against the Miami Marlins at Marlins Park. Mandatory Credit: Steve Mitchell-USA TODAY Sports
“There are lies, damned lies, and statistics.” –Mark Twain
“Statistics show that of those who contract the habit of eating, very few survive.” –George Bernard Shaw
“Statistics are used much like a drunk uses a lamppost–for support, not illumination.”–Vin Scully
One of the ongoing fascinations of the game of baseball is the degree to which it lends itself to statistical analysis.
Perhaps more than any other sport on the planet, the performance of modern baseball players can be captured and converted into a seemingly infinite number of mathematical expressions. Those measurements can in turn be aggregated and used for comparison purposes when evaluating an individual’s performance versus his peers on the diamond.
This is nothing new–baseball statistics have been gathered since the early days of the sport.
But unless you’ve been hiding under a rock lately (and I’ve heard unsubstantiated reports that since early October many Detroit Tiger fans have been doing just that), you are certainly aware there’s been a relentless movement towards applying “advanced statistics” to performance analysis.
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Collectively, of course, these statistics are known as sabermetrics, and in many cases are rather arcane and mostly indecipherable to the average fan.
Not to worry–this is where your friendly Motor City Bengals columnist comes in.
With the off season in a temporary lull before the winter meetings ensue, this is the ideal time for us fans to educate ourselves on these obscure terms. By doing so, we can at least appear knowledgeable about the Tigers at those upcoming holiday parties, while sipping mulled wine and nibbling on artisan cheese.
Wait a minute–this is a baseball article–make that a Ballpark frank and a beer!
In any case, for the sabermetrically-challenged such as myself, here’s a glossary of 25 actual sabermetric terms, along with my translations (I think I got their meanings mostly right, but admittedly I’m no expert and these are complex concepts):
BABIP: A misspelling of “Bo Peep”, the Little Miss of nursery rhyme fame who lost her sheep
BB%: the frequency with which Dick Vitale uses the word “BayBee!” during a college basketball broadcast
BsR: a person who is economical with the truth
Contact%: the number of friends you call successfully on your cell phone
DRS: a group of medical professionals who overcharge for their services
FIP: an annoying person from Illinois
GB%: the Detroit Lions’ winning percentage against the Packers in Green Bay (this value is always equal to zero)
GIDP: what you say to a horse to encourage it to run faster
GPA: what you should have focused on in school instead of the opposite sex
ISO: a term for something not so pretty to look at
K/9: a statistic relevant only during the month of August (i.e., the “dog days”)
LOB: the type of throw delivered by a weak-armed pitcher
MD: see DRS
OOZ: the first baseman in Abbott and Costello’s famous baseball routine
OPS: special undercover operations (e.g., stealing the opponent’s signs)
Pitch Types: an opening line at a bar (e.g., “do you come here often?”)
PrOPS: respect accorded the top players in the game (Cabrera, Trout, etc.)
Pythagorean Record: this one’s totally Greek to me
RZR: a pitch invented by Sal (“The Barber”) Maglie, who was famous for giving hitters “close shaves” with high inside fastballs
SBA: a whirlpool where a player goes after the game to soak his aching muscles
SLG: a base runner who’s totally incapable of stealing a base
UZR: a player who takes Performance Enhancing Drugs
WHIP: given the chance, a weapon Tiger fans would gladly apply annually to the backside of Dave Dombrowski for not fixing the bullpen
wOBA: Joba Chamberlain‘s little-known alien brother
xFIP: an annoying person who used to live in Illinois
So there you have it, a desultory romp through the wacky world of sabermetrics.
Assuming you’re interested in the legitimate meaning of these terms (and a plethora of others), you should consult one of the websites that appear at the end of this piece for further enlightenment.
Be advised, though, that merely having read this article has in no way prepared you to navigate the labyrinth of advanced statistics.
Perhaps the best you can hope for as you step into the sabermetric swamp is to emerge from it on the other side in a conscious state.
Most people do.
Statistically speaking, of course.