Matt Kemp's 2008 Was Pretty Special
Using my new SQL skills (thanks Colin!) I ran a few queries. The one I'm publishing today was simple: since 1900, I wanted the highest BABIPs for players with 450+ at-bats as well as 150+ strikeouts. The at-bats weren't really necessary, unless someone struck out more than 50% of the time, but whatever. I assumed players with high strikeout totals would have more extreme BABIPs because they're obviously putting less balls into play. Little did I know how extreme they would turn out.
Here's everyone with a BABIP over .350.
| Player | Team | Year | AB | H | HR | BB | SO | BABIP |
| Jose Hernandez | MIL | 2002 | 525 | 151 | 24 | 52 | 188 | 0.405 |
| B.J. Upton | TBA | 2007 | 474 | 142 | 24 | 65 | 154 | 0.393 |
| Bobby Bonds | SFN | 1970 | 663 | 200 | 26 | 77 | 189 | 0.387 |
| Mo Vaughn | BOS | 1997 | 527 | 166 | 35 | 86 | 154 | 0.384 |
| Dick Allen | PHI | 1965 | 619 | 187 | 20 | 74 | 150 | 0.367 |
| Mo Vaughn | BOS | 1996 | 635 | 207 | 44 | 95 | 154 | 0.366 |
| Mark Bellhorn | BOS | 2004 | 523 | 138 | 17 | 88 | 177 | 0.365 |
| Sammy Sosa | CHN | 2000 | 604 | 193 | 50 | 91 | 168 | 0.363 |
| Matt Kemp | LAN | 2008 | 606 | 176 | 18 | 46 | 153 | 0.361 |
| Andres Galarr. | MON | 1988 | 609 | 184 | 29 | 39 | 153 | 0.361 |
| Ryan Howard | PHI | 2006 | 581 | 182 | 58 | 108 | 181 | 0.356 |
| Preston Wilson | FLO | 1999 | 482 | 135 | 26 | 46 | 156 | 0.356 |
| Jorge Posada | NYA | 2000 | 505 | 145 | 28 | 107 | 151 | 0.355 |
| Jim Thome | CLE | 1999 | 494 | 137 | 33 | 127 | 171 | 0.354 |
| Ben Grieve | TBA | 2001 | 542 | 143 | 11 | 87 | 159 | 0.353 |
| Jim Thome | CLE | 2001 | 526 | 153 | 49 | 111 | 185 | 0.353 |
| Ray Lankford | SLN | 1998 | 533 | 156 | 31 | 86 | 151 | 0.352 |
See, Jose Hernandez knew he was being highly successful when he put balls in play, so he figured he'd just swing at anything and watch it turn into a hit. Bobby Bonds proves that his family's name is on top of any stat report, ever. Mo Vaughn and Mark Bellhorn represent Boston well (I guess?) and then there's Matt Kemp. The 24 year old who-probably-should-not-play-center-but-had to-because-his-team-cannot-judge-defensive-talent Dodger who hit well enough for an OPS just a tick below .800. Not bad for only his second season with more than 300 plate appearances, even if he did go down on strikes 153 times this season.
For those wondering, Dave Kingman's 1981 season was the lowest with an average of .206. Jose Canseco appears to be the only other player on record with these restrictions and a BABIP below .250, although over the years Rob Deer and Jeff Burroughs gave it a legitimate run.
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20 comments
Comments
By the way...
This post serves as fair warning to all reader’s of RJ’s future abuse of slicing and dicing data. It’s going to get out of control quickly, folks. Not that that’s a bad thing.
Beyond the Boxscore // Calling BJ Upton lazy is lazy.
by Sky Kalkman on Nov 15, 2008 2:10 PM EST reply actions 0 recs
Also,
Kemp had a .411 BABIP last year. Has he simply been lucky for two seasons in a row?
by Peter Bendix on Nov 15, 2008 2:13 PM EST reply actions 0 recs
If he's prone to high strikeout totals...
Then not necessarily. Although at some point I would guess (no data to back this up) his BABIP will have a season of collapse, wouldn’t you?
by R.J. Anderson on Nov 15, 2008 2:18 PM EST up reply actions 0 recs
Maybe your new-fangled database skills can study this question.
What is the year-to-year correlation of hitters’ BABIP? How much should we regress one season’s worth? Two seasons’? What if you include multiple variables, like K-rate, HR-rate, LD%, etc? Once you get season data from your database, Excel can run the multi-variable regressions.
Beyond the Boxscore // Calling BJ Upton lazy is lazy.
by Sky Kalkman on Nov 15, 2008 2:27 PM EST up reply actions 0 recs
It's very possible.
The big thing to learn is joins – I’ve gotten part of the tutorial on joins written up, but it’s a heavy topic to deal with.
To do a simple correlation, you don’t even need Excel. To correlate XR to RUNS (left over from my great run estimator test from a while back), you would use:
((SUM – (SUM * SUM / COUNT)) / sqrt((SUM – pow(SUM, 2.0) / COUNT) * (SUM – pow(SUM, 2.0) / COUNT))) AS R
It’s a bit mealymouthed but perfectly functional.
by cwyers on Nov 15, 2008 11:39 PM EST up reply actions 0 recs
…or it would be, if SBN didn’t eat parts of it. Substitute asterisks for the x’s below:
((SUM – (SUM x SUM / COUNT)) / sqrt((SUM – pow(SUM, 2.0) / COUNT) x (SUM – pow(SUM, 2.0) / COUNT))) AS R
by cwyers on Nov 15, 2008 11:41 PM EST up reply actions 0 recs
Posted a question along these lines over at StatCorner
Inquiring minds want to know.
by Nick J on Nov 15, 2008 11:00 PM EST reply actions 0 recs
Just meant that I had the same question...
How much should we regress BABIP and/or batted ball data when making projections? To put it another way, how much of BABIP (and for that matter batting average) is skill, and how much is random variation/luck?
The guys at StatCorner said they’re working on it. I just find it curious how commonplace the acceptance of DIPS is among sabermatricians, yet nobody seems to have answered the question as to how luck impacts the other side of the ledger.
by Nick J on Nov 16, 2008 8:06 PM EST up reply actions 0 recs
Actually...
That’s not completely true. There HAS been a good amount of research into the luck side of hitting. But I don’t think we’ve really decided how to differentiate between luck and skill when it comes to LD% and BABIP.
In short, good question. I look forward to what people discover.
by Nick J on Nov 16, 2008 8:12 PM EST up reply actions 0 recs
What's wrong with Kemp in center field?
Dewan’s Plus/Minus has him at -1 (16th) and Baseball Musings’ PMoR has him about average. All in all, I don’t see 1/10th of a win being so detrimental that he should be forced to move to a corner.
by kensai on Nov 16, 2008 6:21 AM EST reply actions 0 recs
Optimally he'd play in a corner.
by R.J. Anderson on Nov 16, 2008 10:54 AM EST up reply actions 0 recs
Is it worth it?
Runs wise I mean.
He already has one of the best throwing arms in center, and if he can improve his range marginally to average, doesn’t his offensive production become much more valuable to the Dodgers from center than a corner? After all, it might allow them to field something like Ramirez-Kemp-Ethier or really Any High Priced Slugger-Kemp-Ethier.
I didn’t really look at his RF runs saved. :o
by kensai on Nov 17, 2008 8:51 AM EST up reply actions 0 recs
Matt Kemp
He has to raise his average a little. I don’t think that Man-Ram is going to be in L.A. next year to protect him in the line-up.
The Trade-Maker
by dasox313 on Nov 16, 2008 11:51 AM EST reply actions 0 recs
He was fine
He also had his best month before Manny got there.
Who's world is it? It's yours.
by BlackOps on Nov 17, 2008 12:08 AM EST up reply actions 0 recs

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