Tagged: Dodgers

Does Matt Kemp Really Stink in CF?

Are Ethier and VanSlyke Actually Better?

by D.K. Robinson, 7/22/14

Don Mattingly’s decision to abruptly move Matt Kemp from CF to LF and replace him with a platoon of Andre Ethier and Scott VanSlyke may well go down in history as one of the most curious and potentially catastrophic moved ever made by a Dodgers manager.  For years, many bloggers and fans of sabermetrics have yearned for the day that the managers of their teams would follow their statistical breadcrumbs and start making actual meaningful decisions based on an alphabet soup of acronyms for what are commonly referred to as “advanced metrics.”  Well, be careful what you wish for, because Mr. Mattingly and others in the Dodgers organization have grossly misread the UZR-flavored tea leaves and are now selling out one of the Dodgers’ most valuable players based on an accidental misinformation campaign!

. . . All right, so that’s a bit of an overstatement.  I’ll confess to being a stat geek.  I love sabermetrics.  In fact, I’ve been tinkering with my own metrics since I first discovered Bill James’ writings in the 80s while I was still playing dice-and-charts baseball simulation games.  That being said, I’ve got some serious concerns about UZR, which I’ll get to in a minute.  Now, back to the article . . .

Using UZR to Force Kemp Out of CF?

On May 23, 2014, Bill Plunkett of the OC Register wrote an excellent story with the headline “Kemp’s outfield woes becoming hard to defend.”  Kemp had been benched in favor of Andre Ethier the day before and Plunkett quoted Mattingly as saying “Obviously center field has been a situation we continue to look at . . . We need to get better there. We’re looking at all options.”  Plunkett wrote that “Mattingly acknowledged that defensive metrics like UZR (Ultimate Zone Rating) and D-WAR (defensive-WAR) do not reflect favorably on Kemp” and further quoted Mattingly as saying “I’m certainly not going to sit here and bash anybody or publicly go into the numbers. We know what they are, though.”  Yikes!  Mattingly’s been sniffing the UZR and the UZR’s been making him crazy!

So what, exactly, is this UZR?  According to the popular website fangraphs.com: “UZR is an advanced defensive metric that uses play-by-play data recorded by Baseball Info Solutions (BIS) to estimate each fielder’s defensive contribution in theoretical runs above or below an average fielder at his position in that player’s league and year.”  The raw UZR statistic essentially reflects the number of extra runs a fielder prevents or allows when compared to an average fielder and is cumulative in nature.  So, for example, a player with an UZR of 10.0 has theoretically prevented 10 runs from scoring by his excellent defense when compared to an average player at his position while a player with an UZR of -10.0 has theoretically allowed 10 runs to score that would not have scored if an average defender was manning his position.  UZR’s cousin, UZR/150 projects a player’s UZR rating over 150 defensive games so researchers can estimate what the positive or negative impact of having a player play a position over a full season.

So, what does UZR think of Matt Kemp?  Not much.  Matt Kemp played at least 158 games in CF during each season from 2009-2011 and won the Gold Glove in both 2009 and 2011.  (Yes, I understand that the Gold Glove Awards are often not awarded to the best defensive players in the league . . . but, still, enough managers and coaches thought highly enough of Kemp’s defense to cast more votes for him than any other centerfielder twice in three years.)  Kemp’s UZR ratings for those three seasons were +3.2 (2009), -25.8 (2010) and -4.8 (2011), respectively.  What’s fairly mind-blowing about these UZR scores is the huge discrepancy between 2009 and 2010.  If these numbers are to be believed, Kemp plummeted from being a slightly above-average defender in 2009 to being a butcher who cost his team a full run every week in 2010 and, just as abruptly, rebounded by a full “21 runs” in 2011!  Kemp’s UZR/150 statistics have generally declined since 2011, dropping to -12.6 in 2012, -35.0 in 2013 and rebounding only slightly to -33.6 this season.  Of course, if these numbers are to be believed, no team in its right mind would allow Kemp to play CF as his mere presence there would literally cost the Dodgers a full run every 4th or 5th game.  Not an extra baserunner . . . but a full run!  As I recently continued to read more and more articles citing UZR as the smoking gun that justifies Mattingly’s decision to yank Kemp out of CF, the more the entire premise of the story UZR purports to tell rang false!  I felt compelled to take a fresh look at this “advanced defensive metric” and some possible alternatives.

UZR Has Flaws? – Try P150 On For Size!

Let’s start with the basics:  the primary job of a centerfielder is to field the balls hit to centerfield.  According to FanGraphs, in 2013, the average team had 332 balls hit to CF or about 2.05 CF plays per game.  The Dodgers had the fewest number of balls actually hit to CF (267).  Obviously, Kemp can’t catch calls that aren’t hit to CF!  But how well did Kemp field the balls that were hit in his general direction?  The short answer is: a whole lot better than the press would have you think!

Fortunately, the good folks at FanGraphs have yet another new set of defensive data that can be very helpful in answering that question in detail.  It’s called “Inside Edge Fielding” and it breaks down all of the balls hit to the zone of a particular position by the observer’s sense of how difficult the ball was to catch.  More specifically, it sorts batted balls into a series of categories which I’ll list here with the MLB average success rate for successfully making plays in each category for the 2012-2014 time period:  Impossible (0%), Remote (9.33%), Unlikely (34.2%), Even (59.14%), Likely (84.7%) and Routine (99.37%).

Using this “Inside Edge Fielding” data, I created a spreadsheet to calculate the number of extra plays that an above-average defender would make – and that a below-average defender would fail to make – over the course of 150 full games.  The results were interesting.  Because Kemp has not played a full season since 2011, I used the aggregate of his 2012-2014 statistics in order to have a reasonable sample size.  Based on that data, compared to an average MLB CF, Kemp fails to make 4.3 plays per 150 games.  I’ve decided to call this metric the “P150” – so Kemp’s P150 rating for 2012-2014 is -4.3.

OK, so a P150 rating of -4.3 is not actually good.  In fact, it ranks Kemp in the lower tier of centerfielders – but the statistic itself gives some real world context to how Kemp’s defensive liabilities actually manifest themselves on the field!  There is a huge difference between failing to make a net 4.3 plays per season and being personally responsible for opening the floodgates and (allegedly) allowing 26-35 extra runs per season (as alleged by UZR).  The P150 metric suggests that, on average, about once every six weeks, Kemp fails to make a play that an average CF would make.  And, yes, while you may observe Kemp actually make mistakes more often than that – bear in mind that most of those mistakes are offset by Kemp’s above-average ability to make more challenging plays (e.g., Kemp converts batted balls in the “Even” category 67% of the time vs. the MLB average of 59%).

Mommy, Where Does Data Come From?

By the way, it is important to remember that all of this data is initially logged by human hands who work for Baseball Info Solutions (BIS).  These “stringers” have an extremely difficult job because they must keep track of a multitude of variables on every play.  Consider this excerpt from “The FanGraphs UZR Primer” (http://www.fangraphs.com/blogs/the-fangraphs-uzr-primer/):

“With UZR, if a fielder makes an out, and the UZR engine estimates that it was a difficult ball to field (and turn into an out) by an average fielder at that position, then the fielder will get more credit than if the UZR engine determined that it was an easy ball to field. Likewise, if a batted ball drops for a hit, a fielder will get more negative credit if UZR determined that it was an easy ball to field (for that fielding position) and less negative credit if it was a difficult ball to field. If a fielder makes an error, UZR automatically assumes that it was a relatively easy ball to field, since that is presumably the definition of an error in the first place, so there is no need to incorporate the speed and location of the batted ball and other factors that can influence how difficult a batted ball is to field. In other words, in UZR, errors are treated as balls that are normally fielded by that fielder and that fielder only (the one who made the error), 95% of the time, or whatever the average error rate is for that position and that type of ball.”

Wow, that’s a lot to keep track of while taking in a ball game!  I have no knowledge about how the good people at BIS hire and train their stringers.  I expect that they do an excellent job.  That being said, I have to wonder if the “human element” may ever come into play when these stringers are logging down what they see happen on the field.  For example, if Kemp’s speed allows him to get close to a ball in play that a slower CF would never have a prayer of catching up to, might that ever have an impact on the data the stringer writes down?  I could easily imagine that a well hit ball to the gap that Kemp narrowly misses could be logged as a “failure” by Kemp to make a play when, if Ethier or VanSlyke were in CF, the play would just be logged as a double that one of those guys had to chase down.  Consider that, according to FanGraphs’ data for VanSlyke’s first 128 innings as a CF, there have been zero plays to CF that fall within the “Remote,” “Unlikely,” or “Even” categories and only one play in the “Likely” category.  Perhaps some of the stringers subconsciously realize that, when VanSlyke is playing CF, nearly every ball hit to that zone must either be “Routine” or “Impossible!”

Who Can Prove Whether UZR’s Premise Is True or False?

It’s at this juncture that I would like to issue a friendly request to the sabermetric community:  Can someone steeped in UZR and its methodology please explain how, in 2013, Kemp’s defensive performance could have cost the Dodgers a full 35 runs over the course of 150 games?  Seriously, where would all those runs have come from?  And can someone please cite some actual examples of Kemp’s porous defense causing the opposing team to score runs at a rate anywhere near 35-runs-per-150-games?  And if those UZR/150 do not accurately reflect the true impact of Kemp’s defensive lapses, can someone please clarify that (and explain it to Mr. Mattingly?).  According to the “Inside Edge Fielding” data, Kemp’s rate of converting batted balls into outs was proficient enough so that, over the course of the equivalent of 150 games, the net impact of his defense would have been two failures to make a play that an average CF would have made.  That doesn’t seem like enough to cause opponents to score 35 times.

By the way, it should be noted that when we separate Kemp’s recent partial-year statistics on a season-by-season basis we get some rather curious results.  According to the “Inside Edge Fielding” data, Kemp was actually above-average in 2012 (a P150 of +2.5), somewhat below average in 2013 (-2.0) and horrifically below average in 2014 (-23.4!).  However, I would caution the reader that these statistics can become very volatile when the sample size gets too small and Kemp has only played 326 innings in CF this season (the rough equivalent of 36 games).  I would submit that, given the chance to play CF consistently, as Kemp’s mobility and confidence in his ankle improves, he might at least be able to approach his 2013 level of defense.

Do Ethier and VanSlyke Stink More or Less Than Kemp in CF?

What are the Dodgers’ alternatives?  If Kemp is now a below-average CF, do Ethier or VanSlyke represent improvements?  Ethier has now played over 1000 innings in CF between 2013-2014 (over 120 G) and his P150 is currently -5.3, which is substantially worse than Kemp’s -4.3 for the 2012-2014 period.  Either’s P150 for 2014 is a disappointing -9.6 over 442.1 innings, but that is obviously much better than Kemp’s P150 of -23.4 accrued in 326 innings this season.  VanSlyke’s sample size is hopelessly small (just 128.1 innings, the equivalent of just over 14 G) and his P150 so far is a dreadful -17.5.  What about Puig?  In 55.1 innings in CF (a crazy small sample size), Puig’s P150 is an awful -21.2.

So what should Mattingly do?  First, he needs to free himself from the notion that Matt Kemp playing CF would cost his team anywhere near 35 runs per season.  Second, Mattingly should give some careful thought as to whether or not he believes that, with consistent playing time, Matt Kemp has the potential to just get back to where he was defensively before July 22, 2013 (when he broke his ankle).  Third, Mattingly should pay attention to the fact that Ethier’s and VanSlyke’s limited range in CF make them defensive liabilities with little chance of improvement.

Meanwhile, I intend to root for Matt’s return to CF.  And, failing that, I’ll pray for Joc!

. . .  and, just for fun, here’s a small slice of my initial P150 data (P=Plays, C=Chances):

Player (CF) Innings Remote










P C P C P C P C P C P150
Amarista 647.66 0 4 1 5 1 3 4 5 174 175 -4.26
Ethier 2y 1096.66 0 6 0 8 1 5 8 10 232 232 -5.33
Ethier 14 442.33 0 3 0 6 0 2 4 5 101 101 -9.60
Fowler 2590 3 25 6 13 6 12 21 23 595 598 +1.68
Gomez 2954 4 24 5 16 10 15 31 37 805 810 +0.89
Gwynn 2419 1 6 0 2 1 3 6 8 131 131 -0.56
Hamilton 764 0 7 1 4 2 3 10 11 183 185 -1.77
Kemp 12 911 1 5 1 4 7 8 6 7 193 195 +2.48
Kemp 3y 1813.33 2 10 1 10 10 15 14 20 388 393 -4.32
Kemp 13 576.33 1 3 0 5 3 4 3 5 126 126 -1.95
Kemp 14 326 0 2 0 1 1 3 5 8 69 72 -23.38
Puig 55.33 0 0 1 1 1 1 0 0 9 11 -21.16
Saunders 1676.66 0 12 1 7 2 5 9 11 450 453 -3.28
Trout 2641 4 21 5 6 11 15 27 31 704 707 +4.65
VanSlyke 128.33 0 0 0 0 0 0 0 1 30 31 -17.47


Dee Gordon Deserves A Fair Shot To Win The Dodgers Starting Second Base Job

Originally posted on February 19, 2014 at http://www.dodgersbeat.com/dee-gordon-deserves-a-fair-shot-to-win-the-dodgers-starting-second-base-job/

Dee Gordon Deserves A Fair Shot To Win The Dodgers Starting Second Base Job

Dee Gordon gets a bad rap.

Sure, Gordon played poorly (for three months) in 2012.  Sure, his defense as a MLB shortstop has thus far been, well, poor.  But Dee Gordon is still the guy who, just three years ago, Baseball America ranked as the 26th best prospect in all of baseball.[1]  Two years earlier, at the age of 21, Gordon was named the Midwest League Prospect of the Year and league Co-MVP[2] and Baseball America not only named Dee the Dodgers’ top prospect, but also recognized him for having the “Best Tools” in four categories: Best Hitter for Average, Best Defensive Infielder, Fastest Baserunner and Best Athlete.[3]

Of course, some prospects never live up to their early hype.  But, for goodness sake, there have been plenty of highly-touted young prospects who have experienced growing pains transitioning from the minors to the majors and gone on to enjoy fine careers.  After all, Gordon has never spent more than three consecutive months on the Dodgers active roster during any baseball season.  Perhaps passing judgment on Dee Gordon as a “failed prospect” (as some seem to have done) is premature.  In fact, given the current make-up of the Dodgers’ roster and Gordon’s overall profile, he should be given a fair chance to compete head-to-head with Alex Guerrero to break camp as the Dodgers starting second baseman on Opening Day.  Here are some reasons why:

While Dee’s ups and downs have been well-documented and his “downs” have been roundly criticized by some pundits and other members of the Dodgers blogosphere, his career MLB stats through his age-25 season (2013) would be regarded by many as a very promising debut season (albeit with room for improvement, especially with respect to his OBP).  So far, Dee has 669 MLB PA, which is generally consistent with the number of PA a full-time MLB leadoff hitter would enjoy during a full season.  Here’s what Dee has done with those PA:

669 621 81 159 19 5 2 66 19 37 110 .256 .301 .312 .614

Stealing 66 bases and scoring 81 runs in the rough equivalent of his first full season should have most Dodgers fans salivating for what’s to come.  Unfortunately, because these stats were accumulated piecemeal over fragments of three MLB seasons, the true value of what he’s already achieved is often lost on even the more sophisticated fans, bloggers and writers.

Of course, an OBP of .301 is not going to get it done over the long haul.  But just consider that a starting point that’s primed for improvement for two main reasons: his walk-rate has continued to show significant improvement and, aside from a bizarre slump shortly after he hit his lone HR last season, Gordon spent 2013 hitting well for the Dodgers, the Isotopes, Tigres del Licey (Dominican League) and Indios de Mayagüez (Puerto Rican League).

From 2011 to 2013, Dee has more than doubled his walk rate at AAA and more than tripled his walk rate at MLB.  Not only does this bode well for his eventual ability to sustain a reasonable OBP at the major league level, but it tends to negate the oft-heard rap that Dee is somehow “uncoachable.”  Clearly, this marked improvement demonstrates Dee’s commitment to improve his game.



























So far in his career, Dee Gordon has batted .256 with a strikeout rate of 16.4%.  On May 11 of last season, Gordon capped a great first week back in the big leagues by stroking a HR improving his AVG/OBP/SLG lime to a very solid .269/.387/.462 (after 7 games).  Unfortunately, hitting that HR seemed to cause Gordon to come down with a bad case of Dinger Fever.  Suddenly, Dee’s scrappy game plan yielded to an ill-conceived  swing-from-the-heels approach that dragged him down into a horrific 11-game slump during which he went 0-for-22 with 9 strikeouts (more than double his career rate).  That kind of slump might cause a slight dent in the season stats for an everyday player, but because Gordon spent 2013 shuttling back-and-forth between the Dodgers and the Isotopes, that slump trashed his stat line.  Excluding that anomalous 11-day 0-fer tailspin, Dee’s stat line for all of 2013 would have been a sizzling .306/.358/.389!

Dee was sent down to AAA after that fateful May slump.  But when he returned, he quietly produced excellent results in limited playing time (.355/.394/.387).  In fact, after July, Dee Gordon had the highest batting average on the Dodgers.  That output carried through into the Winter Leagues, first as a member of Tigres del Licey in the Dominican League (where he reportedly played a decent CF) and then as a member of Indios de Mayagüez in both the Puerto Rican League and Caribbean Series (where he reportedly played excellent 2B without making a single error).

Dodgers 2013 (excluding 11-game slump) 80 22 7 12 .306 .358 .389
Dodgers Aug.-Sept. 33 11 2 5 .355 .394 .387
Caribbean Winter Baseball (incl. playoffs) 123 39 9 16 .342 .390 .386

Gordon played Winter League ball through mid-January and, throughout the “off-season” he engaged in intensive hitting and defensive training drills, embraced a weight-training and weight-gaining regimen and spent his “off days” at home working on his stroke in his own personal batting cage reportedly built by his father (sparking memories of Vince Piazza who built a home batting cage for young Mike Piazza).  The Dodgers should give Gordon every opportunity to demonstrate that he’s ready to become an everyday major league baseball player and finally start to fulfill his promise.

While it may seem as though Gordon has been disappointing Dodgers fans for an eternity, he’s still relatively young.  Gordon was arguably rushed to the big leagues in 2011 at the age of 23 and this April he will turn 26.  MLB is full of productive players who did not enjoy a net-positive season before their 26thbirthdays.  Longtime Dodgers fans should remember that the great Davey Lopes did not even play his first major league baseball game until he was 27 years old.  Consider these statistical profiles of Dee Gordon alongside selected contemporary and historical players through their age-25 seasons:








Larry Bowa








Jose Offerman








Dee Gordon








Carlos Gomez (MIL)








Everth Cabrera (SDP)








Leonys Martin (TEX)








It would seem that Gordon is in good company.  Among this group, Gordon has the highest average and the most SB (per 700 PA) through the age of 25.  He is, perhaps, most similar to former Dodger Jose Offerman, with whom Gordon shares much in common.  Both Offerman and Gordon were arguably rushed to the big leagues before they were ready, both were highly-touted minor league prospects, and both became overwhelmed by the task of playing quality defense at shortstop at the major league level.  In fact, when Offerman finally had an offensive breakthrough season (.287/.389/.375) at the age of 26, his reputation for defense at SS was so awful that the Dodgers traded him to Kansas City for Billy Brewer (whom they later flipped to the Yankees for Mike Judd (who posted a record of 3-2 with a ERA of 8.41 and a WHIP of 1.761 for the Dodgers from 1997-2000).

When Jose Offerman joined Kansas City, the Royals moved him from SS to 2B and he became a much more effective defensive player as a second-baseman than he ever was as a SS.  Perhaps not coincidentally, during his three years as the Royals 2B, Offerman posted a tremendous offensive line of .306/.385/.419.  Offerman would go on to have several productive years with the Red Sox (mostly as a 2B).  Had the Dodgers had the foresight to change Offerman’s position earlier – who knows how productive he might have been . . . as a Dodger!

The good news for Dee Gordon is that the Dodgers have (apparently) decided to switch him to 2B or CFnow.  One might well imagine that, freed from the challenge of playing SS, a position for which he just may not be well-matched, Gordon may be much more likely to thrive.  Smart position switches early enough in a player’s career can yield very positive results.  Consider another famous Dodger example:  Steve Garvey struggled mightily as the Dodgers highly-touted third-baseman from 1970-1972, committing 42 errors over 164 games at one point and posting a remarkably dismal fielding percentage of .902 in 1972.  Before 1973, his offense was not too exciting either, as he posted a cumulative line of .254/.304/.397 during that period.  But when the team moved him to first-base in 1973 he quickly became a star player, posting a line of .304/.328/.438 and, in 1974, he was the National League MVP and lead the Dodgers into the World Series!

The current conventional wisdom seems to be that the starting second-base job is Alex Guerrero’s to lose, despite the fact that he’s a career SS who hasn’t played professional baseball in over a year and has never played a MLB game.  Guerrero may become a superstar.  But the decision of which player should become the Dodgers starting 2B in 2014 should be based on merit.  Dee Gordon certainly deserves a fair opportunity to prove that he’s finally made himself into the right man for the job.

D.K. Robinson




Welcome to my blog

Hi there.  I’m a baseball fan.  A Dodgers fan to be more precise.  I’ve named this blog in honor of my favorite Dodgers player since the turn of the century: third-baseman Adrian Beltre.  Oh how I wish that Frank McCourt had coughed up the extra million a year that would have kept Adrian wearing Dodger Blue – perhaps for the balance of his Hall of Fame career . . . instead of saving that money to sign nobody’s favorite Dodger: J.D. Drew.

My perspective as a fan is to try to balance the modern sabermetric view of baseball with certain traditional precepts that pre-date the writings of Bill James.  My youthful obsession with APBA (a dice-and-charts baseball simulation game) evolved into a fascination with early sabermetrics, but today I find that some fans of sabermetrics seem more devoted to advocating for the accuracy and reliability of their treasured acronyms and numbers than they are to the actual human game of baseball.  Many fans don’t seem to realize that modern sabermetrics only capture partial snapshots of the three-dimensional fully-animated elephant that is major league baseball – and while they can be useful tools, sabermetric statistics are just clues to the deeper underlying truths about which players are better and worse, and why.  

In my view, certain sabermetric stats that are relatively easy to quantify (OBP!  OPS!)) are often given disproportionate weight, while other vital parts of the games (e.g., running speed, the ability of pitchers to pace themselves in order to throw more effective innings) are often given too little weight because they don’t easily fit within the boundaries of concise mathematical formulae.  

Sometimes, the very same fans who swear that major league managers make mistakes every day by not following the collective conventional wisdom of sabermetricians defer almost blindly to scouting reports when evaluating minor league talent.  Question their opinions about major league talent and they’ll bury you in avalanche of newly-minted data.  Offer an opinion based on minor league statistics and they’ll retort “don’t scout a stat line.”      

I’ve been active on a few Dodgers blogs over the years, but because my views often differ from the opinions of the majority (or super-majority) of participants in sabermetric-leaning blogs, active commenting in such environments can become an unpleasant chore.  Swimming against the tide of group-think is not easy!  So, I have finally decided to create this humble little space where I can express and archive my views.  If people find it interesting, that’s great.  If nobody finds it, well, that’s fine too.  I’m not setting out to climb any mountains or vanquish any foes.

Thanks for reading.



P.S.  Special thanks to Mike Petriello for the inspiration.