The All-Star Break Batter Shopping List — Batting Average
Yesterday, I identified a group of hitters worth buying for their home run upside, given the discrepancy between their actual HR/FB rate and xHR/FB rate. Today, I move over to batting average, as I identify the hitters whose xBABIP marks most exceed their actual BABIP marks. These are the guys to target for batting average that you may be able to get at a discount.
| Name | LD% | True FB% | True IFFB% | Hard% | Spd | Pull GB While Shifted% | % BIP Shifted | BABIP | xBABIP | BABIP-xBABIP |
|---|---|---|---|---|---|---|---|---|---|---|
| Nick Castellanos | 26.3% | 32.2% | 0.4% | 49.6% | 5.0 | 5.3% | 21.2% | 0.310 | 0.384 | -0.074 |
| Miguel Cabrera | 28.1% | 31.9% | 0.5% | 49.5% | 1.0 | 2.6% | 10.1% | 0.307 | 0.375 | -0.068 |
| Dexter Fowler | 21.9% | 36.9% | 1.6% | 37.3% | 5.6 | 2.7% | 17.9% | 0.268 | 0.331 | -0.063 |
| Ben Zobrist | 16.7% | 28.7% | 2.9% | 34.1% | 2.6 | 9.3% | 24.1% | 0.226 | 0.285 | -0.059 |
| Maikel Franco | 18.2% | 28.4% | 3.7% | 27.7% | 1.0 | 6.3% | 23.9% | 0.215 | 0.268 | -0.053 |
| Shin-Soo Choo | 26.0% | 24.2% | 0.5% | 37.7% | 4.7 | 21.7% | 69.2% | 0.286 | 0.338 | -0.052 |
| Josh Bell | 17.3% | 27.9% | 2.5% | 32.9% | 4.5 | 5.4% | 19.6% | 0.253 | 0.303 | -0.050 |
| Randal Grichuk | 23.3% | 40.1% | 4.6% | 42.7% | 4.5 | 3.8% | 20.0% | 0.277 | 0.325 | -0.048 |
| Matt Carpenter | 22.6% | 48.4% | 2.3% | 45.1% | 2.9 | 14.3% | 75.9% | 0.256 | 0.303 | -0.047 |
| Jose Reyes | 17.7% | 35.5% | 8.5% | 26.0% | 6.7 | 0.4% | 7.5% | 0.222 | 0.268 | -0.046 |
| Brett Gardner | 21.3% | 35.8% | 2.1% | 35.0% | 5.8 | 0.4% | 4.3% | 0.284 | 0.327 | -0.043 |
| Dansby Swanson | 21.8% | 25.8% | 1.8% | 29.8% | 2.3 | 0.0% | 0.5% | 0.274 | 0.315 | -0.041 |
| Jonathan Villar | 18.4% | 21.2% | 1.7% | 34.2% | 5.8 | 0.0% | 2.1% | 0.297 | 0.338 | -0.041 |
| Adam Frazier | 21.9% | 25.9% | 1.0% | 27.7% | 5.2 | 0.5% | 4.8% | 0.286 | 0.327 | -0.041 |
| Francisco Lindor | 18.2% | 40.2% | 2.0% | 35.3% | 4.5 | 2.7% | 10.2% | 0.260 | 0.300 | -0.040 |
Good graces, it’s clear that Nick Castellanos should actually be the best hitter in baseball, as he sits third on my home run shopping list as well. Obviously, I kid, but the guy hits tons of line drives, rarely pops it up, hits the ball extremely hard, has above average speed, and doesn’t hit grounders into the shift too frequently. He has always been a strong BABIP guy, but he should be sitting on a career best mark, not a career low, given the underlying skills driving BABIP. His line drive BABIP sits at a career low of .556, while the league average is significantly higher at .681. Either the stats are telling blatant lies or Castellanos is in for a huge second half.
Miguel Cabrera is 34 years old and his wOBA has plummeted to its lowest mark since his 2003 debut. So it would be easy to chalk this up to age-related decline. But the underlying skills scream otherwise. Yes, he’s swinging and missing a bit more often, but everything else remains elite. I bet you could buy him cheaper than his draft day cost and that would seemingly be a wise move.
It’s rare to see a hitter who gets shifted so frequently still appear as a BABIP underperformer, but look at Shin-Soo Choo! Despite pulling grounders into the shift nearly 22% of the time, he still apparently deserve a BABIP nearing .340! The key here is Castellanosian skills with tons of liners, few pop-ups, power, and speed. The power has been a nice surprise so far, and since he’s been a big BABIPer in the past, there’s real potential for five category production in the second half.
If Randal Grichuk’s appearance atop the home run shopping list hasn’t convinced you to buy in NL-Only leagues, perhaps his appearance on this list too will be the push you need. It’s been a miserable season, and it’s possible that he’s suffered from a bit of bad fortune on both the power and batting average front. He should cost little so he’s worth pursuing in deep leagues.
Matt Carpenter is another double appearer, with both home run and batting average upside. With a line drive stroke and few pop-ups, he should be posting strong BABIP marks annually. The pulled grounders into the shift is the only red flag here.
Jose Reyes is just a better BABIP away from providing all-around category production.
No one really believed that Jonathan Villar would repeat his surprise performance from last season. But a lot of that has simply been a turn of BABIP fortune. But get this — his xBABIP has merely dropped from .345 to .338…he’s nearly the same hitter! He’s still displaying power and speed so more balls dropping like they should be means huge potential value in the second half.
Francisco Lindor opened the first month hot as can be, hitting .309 with seven homers. He only required a .301 BABIP thanks to his power and low strikeout rate. But since, he has batted just .231, driven by a pathetic .245 BABIP. There’s simply no reason for it, so his second half should see his batting average return to go along with some power and more opportunities to steal bases.
Mike Podhorzer is the founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
There is currently an ongoing issue with batted ball readings at Detroit that is causing their hard hit % to be far too high.
http://www.fangraphs.com/community/detroits-batted-ball-readings-are-hot/
Whilst the top two probably have been unlucky, maybe not as unlucky as this table suggests.
Thanks, I had forgotten about this article. I do want to see a definitive answer here though rather than “where there’s smoke, there’s probably fire”. Show me the actual fire! I’ll tweet at the Statcast guys with the article and see if they have an explanation.
Actually really appreciate this being brought up. I decided to initially take a look to see if there was smoke after consistently seeing Tigers players show up on helpful lists like this.
I’ve been hoping the article would gain some traction and we could get an extra set of eyes on it. Thanks for sending it out, Mike.
The article is about hard hit%. Doesn’t that come from BIS and not Statcast?
Seems to me like Mike and I both used the FG hard % number in the articles. Yes, it does look like it comes from BIS, but others can confirm.
Started a Twitter discussion with Mike Petriello and he reminded me that the article is using Hard%, not exit velocity. So different metrics, but he’s still going to look into it. Hard% affects my xBABIP, but not xHR/FB rate, which is strictly Brls/BBE, driven by exit velocity and Statcast.
The issue I have with this is…look at his home/away splits. 62 wRC away, 130 at home. Home stadium is not the problem at all, the problem is an inexplicable home/road split that looks a lot like bad luck.
Villar link takes us to “jonathan Villa”!
My assumption would be that Marwin Gonzalez would be on the BA overachiever list. I continue to be astounded that he continues to pile up massive numbers with terrible peripherals (low LD%, low hard%, high (bad) soft%)
Agreed. I didn’t look at the xBABIP overperformers, but I know he was there on the xHR/FB list recently. He just keeps hitting even though the underlying skills suggest he shouldn’t be.
RE: Matt Carpenter, there is such a divide between this BIS driven xBABIP equation (.303) and the Statcast driven xBABIP equation by Andrew Perpetua’s xStats (.278). This must be because not all non-pop up fly balls are created equal and Carpenter hits too many non-high quality flyballs that happen to not be classified as pop ups by BIS. Surely, Carpenter’s BA should go up from .237, but I don’t think it will make it all the way back to historical levels (.270’s). Not with his extreme fly ball tendencies.
Yeah, each of our equations has its flaws, as his is missing the speed component as well as defensive shifts against, whereas I’m relying on BIS batted ball classifications. His xBABIP has more classifications, which is better. It would be great to combine the two, but his is infinitely more difficult to calculate! At least mine uses all data that could be exported from FanGraphs.
The fact that your equation is calculable from Fangraphs data is really nice. It does mean that your accuracy will be limited by what Fangraphs puts on the site, but please don’t underestimate how useful that is to readers.
Mike,
do you do a midseason update of Pods Projections that project just 2nd half numbers?
I am a subscriber, and would love to do what i did preseason and have a “draft” where I might swap out any of my players for ones on the wire that might give me better standings gain points.
side question: Do you have any idea where “Spin_dir” went on baseball savant? spin rate is nice, but with out the axis, it is kind of useless.
Thanks in advance
Ha, no. All my projections are manual and the preseason ones take months to finish. If I did 2nd half numbers, I wouldn’t be finished until the season ended 🙂
Not familiar with any of the metrics on the Savant exports.
K.
I tweeted DarenW but he isnt responding. If the mood strikes and you are talking to someone who might know, I’d love an answer to that one day.
Thanks Mike
Ask Petriello, he responds to me, haven’t had much luck with Daren myself either.
Villar’s ADP was in the 20s. Plenty of people clearly believed in a repeat.
Heck, I drafted him in the 2nd round in LABR! But 2nd round still isn’t a repeat. He was like a top 5 hitter last year, so we all still priced in some regression.
Is there a way to view stats like xBABIP and xHR/FB Rate when viewing player pages? Or is this data that only Fangraphs writers have access to or something?
No, these are my own proprietary stats so they will never appear on FanGraphs. If I learned how to scrape the stats and have the metrics auto-calculated every morning, I could add some pages to my ProjectingX.com site though.
What’s Anthony Rizzo’s xBABIP? Without knowing anything I’d kinda assume that is .242 BABIP is flukey/unlucky — though maybe his much improved strikeout rate has only come by trading Ks for weak contact?
Can’t remember, but I think when I ran it a month ago, Rizzo was obviously unlucky, but his xBABIP was still below .300.
Good early morning Mike and all. Does Villar lose playing time when Sogard comes back?
Beats me. Prob heavily depends on how Villar is hitting when Sogard is back. Sogard has never hit though so he either learned overnight and his fast start was a complete fluke.
Castellanos has been underperforming the stats under the hood for 2 to 3 years now. I’ll believe the breakout when I see it.