The Curse of Jerry Hairston, Jr./Eric Hinske:
 

Monday, March 14, 2011

Looking Ahead To 2011 - Derek Jeter

Coming off one of the best seasons of his career and in the final year of his contract, Derek Jeter had the worst season of his career, dropping from a line of .334/.406/.465 in 2009 to a line of .270/.340/.370.  It was obviously not realistic to expect a repeat of 2009 in 2010, as you can see by looking at Jeter’s projections heading into 2010.

Jeter’s average projection called for a line of .304/.372/.426 over 629 PA, which would have been worth around 34 runs above a replacement level SS.  Instead he ended up being worth about fourteen runs worse than that.  It’s easy to forget that Jeter actually had a very good April, hitting .330/.354/.521.  From May 1 through September 13 he hit a miserable .247/.323/.338 before finishing the year on a relative hot streak of .347/.435/.389 (fueled by a BABIP of .439).

Jeter set a major league record by hitting 1200 ground balls in 2010.  Actually, that may be a slight exaggeration, but he did hit 65.7% of his balls on the ground, which is 5.7% higher than he had done in any point in his career (data only available from 2002 on).  Ground balls aren’t necessarily a horrible thing, since they’re slightly more likely to be hits than fly balls, but in Jeter’s case it just didn’t work out, whether it was due to him hitting weaker grounders or just having an exceedingly bad string of luck.

If you compare his batted ball data for 2009 and 2010, you can see a pretty clear difference.

Year GB FB LD IFFB
2009 309 123 110 1
2010 364 101 89 2


As a rough rule of thumb, here’s the average outcome for each type of batted ball from 2000-2010.

Type out% 1b% 2b% 3b% hr%
GB 73.1% 21.8% 1.8% 0.1% 0.0%
FB 72.5% 5.8% 8.3% 1.2% 11.5%
LD 26.9% 51.6% 17.6% 1.5% 2.3%
IFFB 97.0% 1.7% 5.0% 0.0% 0.0%


Batted ball data isn’t perfect, because it’s based on subjective assignment by people, so keep that in mind.  We also need to be aware that different types of hitters will have different results with their batted balls.  A Jorge Posada ground ball is not as likely to be a hit as a Brett Gardner ground ball, a Ramiro Pena fly ball is not as likely to be a hit as an Alex Rodriguez fly ball, etc.,

If we look at Jeter’s actual BABIP compared to an expected BABIP for 2009-2010 using the league average rates for each type of batted ball, here’s what it looks like.

Year BABIP xBABIP
2009 .368 .324
2010 .307 .302


This tells me we should expect Jeter to be closer to 2010 than 2009, but I think most of us already knew that.

The raw numbers tell us something, but they’re still kind of limited.  Another thing I wondered about was if Jeter’s actual distribution of where he was hitting the ball was meaningfully different.

Using Baseball Reference’s hit location splits, here’s how 2007-2010 compare.

Year Split PA AB H 2B 3B HR GDP SH SF IBB ROE BAbip BA OBP SLG
2007 Ball In Play 532 527 194 39 4 0 21 3 2 0 16 .367 .368 .367 .457
2008 Ball In Play 511 500 168 25 3 0 24 7 4 0 11 .333 .336 .333 .398
2009 Ball In Play 531 526 194 27 1 0 18 4 1 0 7 .368 .369 .368 .424
2010 Ball In Play 552 548 170 30 3 1 22 1 3 0 7 .307 .310 .309 .381
2007 Fair Terr 540 535 206 39 4 12 21 3 2 0 16 .370 .385 .384 .540
2008 Fair Terr 518 507 179 25 3 11 24 7 4 0 11 .336 .353 .350 .479
2009 Fair Terr 546 541 212 27 1 18 18 4 1 0 7 .370 .392 .391 .545
2010 Fair Terr 558 554 179 30 3 10 22 1 3 0 7 .309 .323 .321 .442
2007 Opp Fld-RHB 91 90 40 12 0 1 0 0 1 0 0 .433 .444 .440 .611
2008 Opp Fld-RHB 109 107 41 11 1 5 0 1 1 0 1 .350 .383 .380 .645
2009 Opp Fld-RHB 119 119 54 10 1 10 0 0 0 0 2 .404 .454 .454 .807
2010 Opp Fld-RHB 123 123 50 10 2 2 1 0 0 0 1 .397 .407 .407 .569
2007 Pulled-RHB 105 104 57 14 0 6 3 1 0 0 6 .520 .548 .548 .856
2008 Pulled-RHB 91 90 34 3 0 2 6 1 0 0 1 .364 .378 .378 .478
2009 Pulled-RHB 84 83 42 3 0 2 1 1 0 0 3 .494 .506 .506 .614
2010 Pulled-RHB 84 84 33 6 0 2 3 0 0 0 2 .378 .393 .393 .536
2007 To Infield 266 263 27 0 0 0 21 3 0 0 16 .103 .103 .103 .103
2008 To Infield 273 266 30 0 0 0 24 7 0 0 8 .113 .113 .113 .113
2009 To Infield 282 278 29 0 0 0 18 4 0 0 6 .104 .104 .104 .104
2010 To Infield 334 333 36 1 0 0 22 1 0 0 7 .108 .108 .108 .111
2007 To Outfield 278 276 179 39 4 12 0 0 2 0 0 .628 .649 .644 .949
2008 To Outfield 249 245 149 25 3 11 0 0 4 0 3 .580 .608 .598 .869
2009 To Outfield 267 266 183 27 1 18 0 0 1 0 1 .663 .688 .685 1.000
2010 To Outfield 227 224 143 29 3 10 0 0 3 0 0 .613 .638 .630 .929
2007 Up Mdle-RHB 348 345 109 13 4 5 18 2 1 0 10 .305 .316 .315 .420
2008 Up Mdle-RHB 322 314 104 11 2 4 18 5 3 0 9 .319 .331 .328 .417
2009 Up Mdle-RHB 346 342 116 14 0 6 17 3 1 0 2 .326 .339 .338 .433
2010 Up Mdle-RHB 354 350 96 14 1 6 18 1 3 0 4 .259 .274 .272 .371

The biggest takeaway from this chart for me is that Jeter has never done well on balls hit to the infield, at least not since 2007.  Of course that’s true of anyone, since it’s just infield singles and ground outs.  The primary problem in 2010 was that he had so many more of them, which again is something I think anyone who watched him in 2010 intuitively knew already.  Basically, if Jeter’s going to be better in 2011, he probably has to stop hitting so many freaking grounders.  We’ll see if the changes that Kevin Long and Jeter have been working on with reducing his stride help with that.

That’s still not granular enough for me, so here’s how Jeter’s balls in play have been fielded by each position over the past four seasons.

Pos 2007 2008 2009 2010
P 5.3% 5.7% 6.3% 6.9%
C 0.5% 0.2% 0.2% 0.3%
1B 3.8% 3.4% 4.7% 5.2%
2B 11.9% 14.6% 12.3% 15.2%
3B 10.3% 14.4% 10.4% 12.1%
SS 18.5% 16.6% 19.5% 20.7%
LF 11.4% 5.5% 9.4% 6.4%
CF 19.6% 17.6% 17.0% 15.0%
RF 18.7% 22.1% 20.2% 18.1%
Left 21.6% 19.9% 19.8% 18.5%
Middle 55.9% 54.6% 55.3% 58.2%
Right 22.5% 25.4% 24.9% 23.3%


Left is just 3B and LF, middle is C, P, 2B, SS, CF and right is 1B and RF.  This table tells me that Jeter was not able to pull the ball as frequently in 2010 as he had in prior seasons, although he wasn’t that far off from what he did in 2007.

Here’s how the projections see Jeter doing in 2011.

Offense

projection PA AB R H 2B 3B HR RBI SB CS BB AVG OBP SLG wOBA BR BR/650 BRAA BRAR BABIP
bill_james 703 641 101 189 31 2 13 68 17 6 62 .295 .357 .410 .342 91 84 7 32 .337
fans 674 618 95 179 27 2 12 72 16 5 56 .290 .358 .398 .340 83 80 3 27 .327
cairo 699 624 99 181 29 2 13 70 15 5 63 .290 .361 .405 .342 88 82 5 30 .322
marcel 641 575 87 163 25 2 12 59 17 5 54 .283 .348 .397 .332 77 78 1 24 .317
oliver 656 587 77 166 24 2 11 65 14 5 56 .283 .349 .387 .329 76 76 -1 22 .319
pecota 710 631 85 177 27 2 12 70 19 6 62 .281 .349 .387 .329 84 76 0 25 .316
zips 648 582 82 163 24 3 12 58 17 5 54 .280 .346 .393 .330 77 77 0 23 .311
average* 671 600 86 170 26 2 12 64 16 5 58 .283 .351 .394 .332 80 78 1 24 .317
2010 739 663 111 179 30 3 10 67 18 5 63 .270 .340 .370 .319 82 72 -5 20 .307


wOBA: Weighted on-base average (does not include SB/CS)
BR: Linear weights batting runs
BR/650: BR pro-rated to 650 PA
BRAA: BR above an average player in projected playing time (adjusted for park, but not for position)
BRAR: BR above a replacement level player (adjusted for park and position)
2010: Un-adjusted 2010 performance  
*average does not include bill_james or fans

Kind of grim.  The projections do think Jeter will be better in 2011, but only by about 5 runs or so.

CAIRO likes him more than most of the other projections.  Here are his percentile forecasts.

cairo % PA AB R H 2B 3B HR RBI SB CS BB AVG OBP SLG wOBA BR BR/650 BRAA BRAR BABIP
80% 734 655 109 197 33 3 16 78 18 6 70 .301 .378 .431 .361 102 90 14 40 .330
65% 713 636 104 188 31 2 14 74 16 6 66 .295 .369 .418 .352 94 86 10 35 .326
Baseline 699 624 99 181 29 2 13 70 15 5 63 .290 .361 .405 .342 88 82 5 30 .322
35% 629 562 82 154 22 1 9 57 11 3 51 .274 .335 .366 .314 67 69 -7 15 .311
20% 559 499 67 129 17 0 6 46 7 1 41 .258 .309 .327 .285 49 57 -17 3 .299


To be honest, until I see something that makes me think differently, I have to assume Jeter’s going to be closer to that 35% forecast, which is around what he did in 2010.

Defense

Jeter won his fifth Gold Glove in 2010, which should tell you all you need to know about his defense.  Either that, or it tells you how useless the Gold Glove awards are.

Player Jeter, Derek
Pos SS
year G Inn DRS zRS uRS tRS avg rARM
2006 150 1292 -18 -5 -7 -5 -9 0
2007 155 1318 -23 -20 -18 -22 -21 0
2008 148 1258 -9 3 0 0 -2 0
2009 150 1260 2 -3 6 4 2 0
2010 151 1285 -13 -18 -7 -12 -12 0
avg 151 1283 -12 -9 -5 -7 -8 0
w_avg 151 1278 -10 -9 -3 -7 -7 0

DRS: Defensive runs saved compared to average using John Dewan’s plus/minus system
zRS: Runs saved compared to average using Chris Dial’s zone rating system
uRS: Runs saved compared to average using UZR
tRS: Runs saved compared to average using Total Zone
rARM: Runs saved with arm compared to average (OF only)
avg: average from 2006-2010
w_avg: weighted average from 2006-2010 (5/4/3/2/1 weight)

You need to remember that when you’re looking at these numbers, they are comparing Jeter to his fellow shortstops.  He just doesn’t compare well to his peers in any of the defensive metrics.  We also need to remember what these numbers are telling us.  They’re not saying Jeter misses two or three plays a game.  An average of -7 for the season means Jeter’s missing something like one play every four weeks.

Like I’ve said before, when all the metrics basically say the same thing, I am willing to trust them.  The thing is, it’s possible Jeter may actually be even worse than these numbers show, as Colin Wyers has done some research that shows a possible range bias by the people who track defense.  I have no idea how much worse that might make Jeter, but I’d also assume if he becomes that obviously bad he won’t be playing shortstop full-time.


Base Running

Year ga_opps ga_r aa_opps aa_r ha_opps ha_r oa_opps oa_r total_opps total_r
2007 38 0 58 1 56 3 462 0 614 3
2008 35 0 54 1 58 1 389 -1 536 1
2009 42 0 77 -1 65 1 554 -1 738 -1
2010 38 -1 54 1 63 0 498 1 653 2
Proj 39 0 61 0 62 1 489 0 651 1


ga_opps: opportunities to advance on grounders
ga_r: run value of advances on grounders
aa_opps: opportunites to advance on air outs
aa_r: run value of advances on air outs
ha_opps: opportunites to advance on hits
ha_r: run value of advances on hits
oa_opps: opportunites to adance on other (wild pitches, passed balls, etc.,)
oa_r: run value of advances on other
total_opps: ga + aa + ha + ao opportunities
total_r: total run value of non-SB base running, compared to average

Between his SB and non-SB base running, Jeter’s still an asset, although that’s less likely to hold true as he ages.

We’ll be hearing about Jeter’s run at 3000 hits for the first few months of the season, which is bizarre since it happened on June 5th of last season.  But to humor those who don’t realize it, Jeter should probably be close to getting his 3000th hit by the second week of June.  June 7 through 9 is a three game home series with Boston, and that seems like a good time for it to happen (for the second time).

I’m somewhat pessimistic about Jeter going forward, because even if his offense gets better his defense is almost certainly going to get worse.  It doesn’t mean I dislike him.  If I was him I’d play until they ripped the uniform off my back.  It’ll be up to the Yankees to figure out how they want to handle the scenario where Jeter begins actively hurting the team if/when it manifests itself.  I don’t think that will happen in 2011, but I’m positive it will happen before he retires.

--Posted at 8:01 am by SG / 36 Comments | - (0)

Comments

Page 1 of 1 pages:

Did you switch FB and GB in the 2nd table? (green header)

Jeter is my favorite player, so ha.

I’m somewhat pessimistic about Jeter going forward, because even if his offense gets better his defense is almost certainly going to get worse.

I’m cautiously optimistic, about the bat at least.  If Jeter’s problem has been loss of quickness, the changes being implemented should help.  If it is batspeed through the hitting zone, we’re in trouble.  Long seems to know what he’s doing, and seems to think it is the former.  No, we won’t see 2009 again - at least not without a fluky-high BABIP - but I think we can still get a productive hitter.

Did you switch FB and GB in the 2nd table? (green header)

Oops, yeah.  I’ll fix it.

The analytics show that four years of suck awaiteth us.

His intangibles are off the chart.

“An average of -7 for the season means Jeter’s missing something like one play e
every four weeks.”

That should be invisible.  I would have thought he misses a play an average SS makes more like once a week, judging from the local commentariat reaction at least.

Apropos of nothing, this is sad.

“An average of -7 for the season means Jeter’s missing something like one play every four weeks.”

That’s interesting, because I’m certain that we all point out missed plays on Jeter’s part far more frequently than that.  Like practically every game. 

“To be honest, until I see something that makes me think differently, I have to assume Jeter’s going to be closer to that 35% forecast, which is around what he did in 2010.”

That may be, but I’m curious as to why the baseline projection doesn’t represent your best estimate of a player’s performance.  Or at least your best estimate not taking into account any subjective considerations.  In Jeter’s case, I would trust the projections as an estimate of what to expect from Derek assuming he continues on the path he’s been on over the last several years.  However, I would probably adjust that estimate UPWARD based on the work he’s doing to shorten his stride.

What I want to know is, what can Long do to ensure Jeter a fluky-high BABIP?

Rilke - that he played FOR FREE for the first 8 years of his career?

[8] That is almost the ultimate test.  However, the real ultimate test is whether or not you can survive death.  So far don’t nobody we know have passed the ultimate test.

[9] That his career high in IP was his rookie season at age 20, 218 IP.

Link for Pin.

“However, the real ultimate test is whether or not you can survive death.”

According to the cover of the tabloid at my local grocery store, Charlie Sheen has done this four times so far this year.

SG,

In the balls in play by fielder table I think you made a mistake in the 2010 column—everything else should be 0%, and shortstop 100%.

Kidding aside, where did you get this data? All season long last year I was dying to be able to proclaim that Jeter led the league by a mile in groundouts to shortstop on the first pitch—don’t know if your data breaks it down by count, but this is the first time I’ve seen a breakout like this of ball in play by fielder.

where did you get this data?

If he told you that, he’d have to kill you…

I was dying to be able to proclaim that Jeter led the league by a mile in groundouts to shortstop on the first pitch

...oh. Never mind.

Regarding the possible range bias - wouldn’t this affect all shortstops equally? Unless the bias is specifically aimed at Jeter, since the stat is comparing all players at a position wouldn’t system wide bias disappear?

[15]  I believe the idea is that if Bad Shortstop A’s range is bad, the observers, seeing him not even try at a ball, will score it a non-fieldable chance instead of taking into account that Average Shortstop B would have gotten to that same ball.

Or will think, Bad Shortstop _couldn’t_ be that bad, etc.

Banuelos starting tonight against the Red Sox.

Fanboy pants explosion in 5, 4, 3, [two fingers], [one finger], [twirl finger].

That should be invisible.  I would have thought he misses a play an average SS makes more like once a week, judging from the local commentariat reaction at least.

It could be confirmation bias, or the fact that he’s not getting dinged as much as he should for plays he’s missing.

Kidding aside, where did you get this data? All season long last year I was dying to be able to proclaim that Jeter led the league by a mile in groundouts to shortstop on the first pitch—don’t know if your data breaks it down by count, but this is the first time I’ve seen a breakout like this of ball in play by fielder.

Retrosheet’s play by play data.

Regarding the possible range bias - wouldn’t this affect all shortstops equally? Unless the bias is specifically aimed at Jeter, since the stat is comparing all players at a position wouldn’t system wide bias disappear?

No.  Where range bias would appear would be on chances deemed as fieldable.  In theory every shortstop should have the same zone, but it may be that Jeter’s lack of range is causing whomever is recording his defensive stats to not necessarily be marking down all the missed plays that a player with greater range would be getting to.

Don’t the recorders have a grid of the field where they mark down the place an average SS would field a particular chance?  I’d naively expect that to quite limit bias.  Hmm, they have to estimate the speed of the ball too, and maybe a little about how it bounces, and the field conditions and grass vs. turf.

Where range bias would appear would be on chances deemed as fieldable.

To add on to that, the idea that I think guys like Mike Fast, Colin Wyers, and others are looking it, has to do with cameras.  That is, the camera focuses on where the ball is, and generally has very narrow view of the field.  Often meaning that there aren’t any reference points.  So two balls hit in exactly the same place up the middle, but the 2nd base bag isn’t in the camera view.  Jeter doesn’t enter the picture in one, so the stringer marks it as unfieldable (close to the 2B bag).  Tulo gets in the picture and the ball just goes under his glove, so it is put in a zone much closer to where the SS ends up.  Jeter gets no or a very small negative, Tulo gets a much larger negative.  Field F/X will (theoretcially) fix this.

Don’t the recorders have a grid of the field where they mark down the place an average SS would field a particular chance?  I’d naively expect that to quite limit bias.

They do, but the field’s not marked, so they’re estimating the zones visually.  The impact isn’t necessarily huge.  Again, we’re talking something like 10 plays out of say 500 over a full season.

Hmm, they have to estimate the speed of the ball too, and maybe a little about how it bounces, and the field conditions and grass vs. turf.

Right, speed of the ball plays into the more advanced metrics.  Not sure about field conditions and bad hops.

That may be, but I’m curious as to why the baseline projection doesn’t represent your best estimate of a player’s performance. 

Because my subjective opinion is not based on algorithms and data.

[23]  Stats not scouting!  Stats not scouting!

Stats not scouting!  Stats not scouting!

OK, I can do that.

Basically, I feel that Jeter’s projection is high because I think the peripherals of his 2009 performance indicate a fair amount of good fortune.  Because 2009 is almost 30% of his 2011 projection, if it was in fact more luck than skill, he’ll project higher than he should.

Kind of like with Cano and Swisher in reverse, where I think their 2008s are suppressing their projections.

How do the various projection systems take calm eyes and will to win into account? Seems like a big miss.

And how subjective is the distinction between “calm eyes” and “no fire”?

[27] You usually adjust for “no fire” based on observing “inappropriate smiling when team is losing” or “slumped shoulders while lazily jogging after a ball you booted” and cross tabbing it with DominicanFx data.

and cross tabbing it with DominicanFx data.

Zing!!!!!!

*honks horn* *drives off in clown car*

The green table is still showing a fly-ball as a more likely base hit than a ground-ball.  I think that’s still backward.

Banuelos starting tonight against the Red Sox.

Live on espNESN for folks like myself who don’t live in the NY area and wait until right before the season to purchase mlb(dot)tv. 7PM EST/4PM PST start. Considering who is starting, I vote a gamechatter complaintchatter is in order.

Did SG or Jon play APBA or Stratometic as kids?

32 against Aceves

[34] This time… it’s personal.

Did SG or Jon play APBA or Stratometic as kids

I did not.  I did play Microleague and Hardball though.

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