The value and interpretations of in-play averages (or BABIP) is one of the more contentious topics here on Getting Blanked. Dave Gershman posted a graphic that sparked a hearty debate which continued when discussing the hot starts of Matt Garza and Brett Wallace as well as an uncharacteristically slow start from Ichiro!
The basic (yet hotly contested) idea is as follows: both hitters and pitchers are susceptible forces beyond their control when the ball leaves the bat. Pitchers can expect balls to find gaps and holes at a somewhat steady rate (as a collective) while hitters individual profile and skill set impacts their personal rates much more.
In both cases an element of luck and random chance joins the mix. Hard hit balls wind up being caught, dribblers make their way through. Group a few weeks (or months) of this together and suddenly you have a career season or a year to forget.
“Famed” SABR researcher (and poet, I assume) Tom Tango wrote a post on his The Book blog recently about this very subject. He mentioned battling with Angels fans when discussing the in-play average of pitcher Jered Weaver. Weaver got off to a torrid start, helped along by a very low BABIP. Angels fans on Halos Heaven believed it would stay low, Tango stated it would come up (it did.) Here is the money quote on the subject:
It’s not like we saberists just decided to believe that a low BABIP is unsustainable. We studied the issue. We relied on actual past performance. We relied on the data that the players themselves produced. All we are saying is: here, take a look at the weight of history, and before you decide to bet against what’s always happened, YOU tell us why this time, it’s “different”.
I realize some feel as though this is pseudoscience, an overcomplication created by fart-sniffing tall foreheads in love with the sound of their own fingers dancing across the calculator keys. Others might be wary, wondering how all pitchers could surrender hits at similar rates.
One key comment from a previously linked comment section echoed this concern, wondering how getting a hit off Roy Halladay could be equally likely to reaching base against a Jo-Jo Reyes-style tomato can. To you I offer one man: Pedro Martinez.
At the turn of the century, Pedro Martinez turned in two of the greatest seasons in baseball history, especially when one considers the balloon-ball era in which he competed. In 1999 he was at the top of his game.
Even playing in the notorious Fenway bandbox, Pedro dominated. He struck out more than 13 batters per 9 innings, walking fewer than 2. He gave up just 9 home runs in 213 inning pitched. He amassed 13 WAR, a staggering number I can barely comprehend.
In a year where the league average BABIP was .298 and his team’s in-play average was .287, Pedro Martinez posted .323.
Pedro faced 835 batters. 313 struck out1, 37 walked, 9 hit nine batters and served up 9 home runs. 12 batters reached on errors. The rest reached on 132 singles and 28 doubles. For the season he gave up 56 runs2.
The very next year, Martinez posted very similarly ridiculous numbers in terms of strikeouts (284) and walks (32). He pitched just four and a third additional innings. He gave up 8 more home runs. For the year 2000 season he gave up just 42 runs. He allowed only 92 singles and 18 doubles. How? His BABIP? .235.
Was Pedro Martinez easier to hit than 1999 versus 2000? I think we can assume not, though the extra home runs might say otherwise.
It is important for to not fear a key principle of life: [GETTING BLANKED] Happens. Even across 400 balls hit weakly off one of the greatest pitchers of our era, sometimes the ball finds some green and sometimes it doesn’t. Every year some players experience dips in their numbers fueled by little more than random chance.
Ducks snort. Texas Leaguers are lost in the Texas sun. Seeing-eye singles get blind drunk. Outfielders like Franklin Gutierrez turns gappers into Dead Flying Things while designated hitters masquerading as left fielders play fly outs into doubles. It happens, sometimes in bunches and sometimes to players deserving much better fates.
The sooner we embrace this randomness, the sooner we can dispatch with semantic arguments on the merits of in-play averages and the like. The vast majority of advanced stats are designed to isolate the true talent elements of performance. In play average is just another piece of the puzzle which helps us better understand and enjoy the game we all love.
1 - lol.
2 – lmao