Disclaimer: I am just pushing this out the door because I know I'm not going to come back to edit this. It could be a lot better written- but I think the point is here.
I had a brief twitter interchange with stlcardinalsfang this morning (4/22) after he posted a depressing Fangraphs link showing the Cardinals team wRC+ this year at 88 (23rd in the majors) - a far cry from an NL-leading 106, 108, and 112 in 2013, 2012, and 2011, respectively (hat tip to Craig Edwards' post from a few days ago for pointing out that these all lead the league), and it got me thinking.
The subject of the interchange was BABIP - specifically, the Cardinals' 2014 team BABIP, which is sitting at .288 as I write this post. This is good for a mediocre 20th in the league - but obviously, it's early. However, when you start digging around, some interesting things pop up.
MLB average BABIP has been quite constant over the past half decade, ranging between .295 and .297. Within my lifetime, BABIP has ranged a bit more, with a low of .283 in 1989, and a high of .303 in 2007. Based on these numbers alone, we might look at the Cardinals' 2014 BABIP and think that it is a touch low.
The Cardinals have had noticeably above-average team BABIPs in the past three years - .314 in 2013, .316 in 2012, and .305 in 2011. At least 2013 and 2012, I think, are relatively representative of the 2014 team and the statements I'm going to make later in this post.
Pizza Cutter's research on sample sizes indicates that for a given player, 820 balls in play is roughly the stabilization point for BABIP - which indicates that over a given season of data, BABIP is not necessarily predictive/stable for an individual player. This probably makes intuitive sense for those of you familiar with BABIP - quite a few individual players have high-BABIP seasons one year, which lead to unsustainable performance, then see regression the next year.
While I, to be honest, have no idea if these concepts can be applied to players in aggregate, it is pretty clear that an individual team would have vastly more than 820 BIP in a given year, which would make me believe that team BABIP is, barring large roster/playing time changes midseason, relatively stable over a given year.
Given this and that many of the 2013 Cardinals' (BABIP = .314, as a reminder) starters are still on the team/starting in 2014, we might look at the 2014 Cardinals' BABIP and think that it is more than a touch low. Well, guess what - I don't have an answer for you - there are way too many factors! Some of them:
- Everyone who was on the team last year is now a year older and BABIP generally peaks younger - but when you actually look at the results, the 2013 Cardinals 29 and younger had an aggregate BABIP of .310, while those 30 and older had an aggregate BABIP of .319!
- We added two new starters (or one and a half starters, maybe) in Peter Bourjos (.309 career BABIP) and Kolten Wong (.299 ZiPS projected 2014 BABIP, very high minor league BABIPs) who I would conventionally think of as high BABIP players - but they're nominally replacing Jon Jay and David Freese, two historically phenomenal BABIP performers (.340 and .342 respectively).
- Carlos Beltran's (.314 2013 BABIP, .303 career BABIP) innings are predominantly now being taken by Matt Adams (.345 career BABIP1) and Allen Craig (.338 career BABIP2)
So really - who knows! Looks me to, in a vague sense, like a wash from prior years - I'd expect a higher BABIP than league average, but probably lower than previous years - so maybe in the .305-.310 range? But I'm just spitballing - I can't predict that.
But this stuff is stuff that bounces around my head all the time, and probably bounces around a lot of your heads all the time too. This morning, however, I made more firmly a connection I had vaguely conceived of before - WHY does this happen?
Well, let's take a look at the 2013 Boston Red Sox and their league leading .329 team BABIP. Where does it come from? Here are your 2013 Boston Red Sox with 500 or more PAs:
|Player||2013 PAs||2013 BABIP||Career BABIP|
Every single player with 500 PA+ outperformed their career BABIP by ten points or more. If you drop the cutoff even lower, you see players like Mike Carp (243 PAs, .385 BABIP), Jose Iglesias (234 PAs, .376 BABIP), and Jarrod Saltalamacchia (470 PAs, .372 BABIP) helping to drive an unsustainable team BABIP driven largely by individual players having outlier seasons, some of them extreme.
Now, let's take a look at the 2013 Cardinals and their league leading .314 team BABIP. Where does it come from?Here are your 2013 Cardinals with 500 or more PAs:
|Player||2013 PAs||2013 BABIP||Career BABIP|
Here, things are not so clear. Yes, Allen Craig had a massive outlier of a season, Yadier outperformed, Beltran had a 11 point bump, and Matt Carpenter probably significantly outperformed what his BABIP will be going forward, although it is hard to know, but Jon Jay, Matt Holliday, and David Freese all significantly underperformed their historical BABIP.
But there is one pretty noticeable factor - the career BABIPs. Take a look at the Cardinals. Those numbers are really high. Not Yadi, and not Beltran, but otherwise? Outrageously high. Matt Adams is similar (.348 career BABIP).
Out of 3,798 qualified players in the history of MLB, according to Fangraphs, Matt Carpenter (#26), David Freese (#60 [and plummeting]), Jon Jay (#67), and Allen Craig (#89) are all in the top 100, or top 2.5%. Matt Adams would be #34 all time if he was qualified. If we restrict this to non dead-ball era (1919-present), they come in at #12, #38, #45, and #62 respectively (Adams at #20) - all in the top 2% (out of 2965). Yes, I expect regression. Nevertheless, these are still really, really freakin' high BABIPs.
Seems pretty crazy to me that this concentration of high-BABIP players have all come together without something pushing them there. Even crazier that all of these players are home grown. Have we made a deal with the devil? Or is this just good scouting. I don't know anything about how one scouts BABIP - but it sure seems like something's going on.
I recognize that I haven't been thorough here (and a little less than organized), and hopefully some of you can help me fill in the blanks. I also recognize that I'm missing a big, big piece of this, which is batted ball data and maybe the concept of xBABIP - I am not comfortable with batted ball numbers, really, and I would like to think that they could tell us a lot about the information above.
1 Small sample size warning - only 487 career PAs and way, way too few BIP to draw any type of conclusion. FWIW, ZiPS projected him to have a high .322 BABIP in 2014, and his minor league BABIPs are also exceptionally high
2 Still probably not a big enough sample size, but getting a lot closer
3 Well over half of career PAs in 2013 - this number is driven pretty much entirely by 2013 BABIP
4 Segmented career - .309 BABIP 2007-2013, very low beforehand