The Ins and Outs of Infields

I knew you were the right man for the job! Great post Paul, as usual. The only thing that bothers me is that WE always have to bend for these old timers. Why can’t they recognize that there are formulas and data out there that summarizes a players ability (for the most part) and in usually pretty darn accurate. Instead we have to just accept that these ideas are just too far fetched.
Is Conlin the guy who used to be on The Sports Reporters years ago?

Cano 15th and cost us 5.2 runs? Wow. No way.

UZR for some reason seemed to undervalue tex and cano last season. I actually mentioned this at some point. As someone who watches almost every game, I find it basically implausible that these guys can be considered defensive liabilities. Perhaps not the very best in their positions but certainly not below avg.
Im not sure about all the ins and outs of the defensive metrics but the one that baseball reference uses says that Tex’s defense was worth 7.2 runs over 1200 innings last year and Cano was pegged at 8.1. (Pedroia was 8.6 for reference purposes). So one can decide what to take and what not to. I would be interested to see how the systems that the teams use to measure defense stack up these various players.

“If you disbelieve the data, then check it out. Simply falling back on your deceiving eyes and imperfect memory is not a particularly effective means of analysis.”
Ouch dude…deceiving eyes and imperfect memory? At least you aren’t smug much Paul. OK, Tex is the 15th best 1st baseman. Laughable.

Further to that point, the fact there is disagreement between the systems and value of various players should say that simply basing ones conclusions on particular statistic is not a particularly effective means of analysis either.

I think we all need to realize that UZR is very, very far from perfect, and needs to be taken with a salt mine’s worth of salt.
From a purely offensive standpoint, the 2009 Yankees most likely had the best group of players in the modern era of baseball. The 2009 Phillies don’t even come close to that designation. That gap widens even more if you decide to include catcher.
Defense-wise…we just don’t know. And since we don’t have the ‘F/X’ data from historical seasons…we likely never will. It does no one any favors to speak in any way definitively on this topic. Defensive statistics are a very, very far way from being definitive. Please, for the sake of argument, let’s treat them as such.

Just because you measure something doesn’t make the measurement accurate. If the thermometer is off it doesn’t matter how many measurements you take, most especially if the error isn’t regular. Variability also has another name: Unreliable.
Hitting is a refined enough skill, measured over a very big sample, that it’s hard to argue what the numbers show. You either hit the ball or you don’t. The same can not be said of fielding. Defense has too many degrees of freedom to be truly quantifiable at this time. The new cameras will help with questions of range, but that’s only one component of defense.
Another reason I doubt the defensive numbers? Jeter. If a player can go from well-below average to well-above average based on some off-season exercises, then how are we measuring a quantifiable skill? That level of variability makes me very skeptical of the whole exercise.
For an example closer to a SF heart: Do you really think Ellsbury was one of the worst centerfielders last year? Or are you going to make a gerrymandered distinction between outfield and infield defense? If anything outfield defense is easier to measure. It’s almost all about range. I guess that’s why the Sox chose to move the younger player to the much easier LF position.
Between Jeter’s “excellence” and Ellsbury’s “horrid” range, that variability is sufficient for me to deem the defensive stats, so far, unreliable.

“Conlin is still OFF HIS ROCKER.”
That’s obvious. NoMaas has the results of emails a fan sent him. Needless to say, the guy doesn’t respect his readers.
“There’s a lot of single-year variation in UZR, krueg, and most people recommend taking three-year samples.”
And yet, three-year samples are so degraded that everyone will regress to the mean. Which three year sample do you take for Jeter? Or for Ellsbury which one year do you believe, because averaging across his three years masks the finding that he’s horrid (2009). Or is he actually awesome (2008) or average (2007)? Oh, he’s somewhere in between? How helpful…

Let me say it again: GREAT POST PAUL. Fantastic perspective on Conlin’s assertions. I’m surprised at the level of disappointment some here are expressing when a stat associated to a player “don’t look right.” Well, if you don’t like the numbers, don’t look at them. There’s no requirement that you do to enjoy the game.
> Just because you measure something doesn’t make the measurement accurate … thermometer
That’s an simplification of a dynamic, evolving, robust, open system with constant critical evaluation from people diligently working to improve the tools available and from those chipping/chirping at it from the periphery.
> Jeter
*Eyes Glaze Over* *furble mumble something intangible something*
Bill James didn’t stick a meat thermometer up Derek Jeter’s ass on a Thursday day-night and decide he didn’t have range. Good thing the world doesn’t own just one thermometer or one set of eyes to read it.
If you get pissed off because some resultant number doesn’t please you, don’t be pissed off at the numbers. Either get educated and involved in the process to help understand it, or Just Watch the game and forget about the stats. Or both.
Great post.

“If you get pissed off because some resultant number doesn’t please you, don’t be pissed off at the numbers. ”
I certainly wasnt just pissed off at the numbers, I just showed how they arent always to be trusted given their volatility.

ag, are you referring to one of my posts?

“They are all just numbers. They only get volatile when someone hangs an adjective on them, and someone else takes it personally.”
Are you being facetious? Measurements can certainly be volatile, variable, unreliable, etc. Pick your own adjective. Just because something is measured doesn’t mean there’s truth there if we just look a little closer.
Go look at Ellsbury’s CF numbers. They’re so variable I just don’t know how they could be describing the same player. But they are. So what am I supposed to take away? That we won’t know Ellsbury’s true defensive contribution until 2013? When he’s in his mid-30s?

I dont believe its fair to say Statistics can tell the whole story and watching the game means nothing.
If you can find where I said that, I’ll retract that sentiment. What I said, and certainly meant, was that if data don’t agree with what you think you’ve observed — and what is data but the numerical (or otherwise) recording of observable events? — then test both the data and the observations.
I think UZR is now suffering at the hands of some who don’t like what it has to say. Those saying that larger sample sizes are “degraded” are not interested in having an intelligent discussion. Those picking out isolated examples of wide variation as a way to discount the use of a statistic are also not interested in having an intelligent discussion. Oh wait, that’s all the same person.
OK, Tex is the 15th best 1st baseman. Laughable.
Almost as laughable as dismissing contradictory data without actually researching the case first. I know, I know, it snowed in NYC this year, so global warming is bunk, right?

Here is a different fielding metric, this illustrates how unclear these metrics can be and also why i have long held a skepticism of UZR.
From baseball-reference.com: (i only had a chance to look up the top few you listed) Here is the statistic they give for total fielding runs above avg for 2009:
1. Adrian Gonzalez 11.7
2. Mark Teixeira 7.2
3. Kevin Youkilis 6.4
4. Derrek Lee 2.2
5. Paul Konerko 2.2
6. Kendry Morales 1.5
7. Miguel Cabrera -1.7
8. Carlos Pena -11.0
This list is pretty different than the one that UZR generated. Youk’s number would be higher if he had more games at 1b for sure. Sorry there hasnt been the time to be more comprehensive but I do believe this makes my point.

ag, I asked because I had an early comment in this post saying I was skeptical of the UZR values.

“That numbers vary from year to year seems like nothing but reality to me.”
That’s exactly the point. And that’s why they play the games. For as good as the projections and statistics might be, they don’t tell the whole story. The games do. Aren’t the best projections looking at an R-squared of .6? That’s a lot of variability. And hitting is easiest to know – lots of data in a restricted, controlled setting. Pitching is much tougher. Defense is still pretty bad.
” Those saying that larger sample sizes are “degraded” are not interested in having an intelligent discussion. ”
Where’s the backup to that assertion? An average of two extremes isn’t an average at all. Yes, the “sample” is bigger. But the underlying cause for the variability hasn’t been explained any better. The average makes something seem more certain when it is anything but. In statistical parlance it’s called the standard error of the mean.
“Those picking out isolated examples of wide variation as a way to discount the use of a statistic are also not interested in having an intelligent discussion.”
Again, where’s your backup? If the measurement is accurate the wide variability wouldn’t be there. We can’t simply choose when to accept certain numbers as valid then ignore other.
“Almost as laughable as dismissing contradictory data without actually researching the case first.”
How is this different than what you’re doing for Ellsbury and Jeter? Either the data is flawed or the players are wildly inconsistent year-to-year. Either way, you’re building a case on faulty assumptions.
I’m all aboard for the offensive analysis. But the defensive metrics just aren’t there yet, if they will ever be. I’m dubious based on complexity theory. There are just too many degrees of freedom to really nail it. But the new cameras will help, especially in the outfield. Still, for Ellsbury to swing almost 40 runs in one year highlights the huge problem.

UZR is suffering, Paul, because people are using it in statistics like WAR, which they then use to make definitive statement’s about a player’s value. UZR should never, ever be stated in a definitive manner, because it’s not definitively correct. There is too much wrong with it. Which isn’t to say it’s not better than other defensive statistics, it likely is. But, just because it’s the best we have doesn’t mean it’s in any way correct. We should all wait for the ‘Field F/X’ (or whatever they’re going to call it) data to come through before we start taking defensive statistics altogether seriously.
Don’t try and paint us ‘non-UZR-believers’ in the same stroke as those who don’t want to believe in, say, OBP as being valuable, in saying that the only reason we don’t like UZR is because we don’t like what it says. I’ll take a page right out of your book and say that anyone who does that is not interested in having an intelligent discussion.

> In statistical parlance it’s called the standard error of the mean
In COLLEGE, I failed stats well enough to know that for deviations, I could take it or leave it, as it were.
No, for me, I liked drama, especially stories in which the Charlatan held court.

The problem isn’t with best or worst cases. The problem is with the huge group of people in-between – over 80% if you assume a normal distribution.
And again, a three-year average with wildly divergent numbers just obscures the problem. That’s simple statistics.
The problem with WAR is indeed in the defense. Answer this for us: What’s the difference in WAR for Teixeira assuming his best defensive season and his worst?
That all said, there’s an assumption here that we just need better statistics. But what are the variables that could cause a defender to go from really good to really bad in one year? If those are things out of his control, and I think they are, then I don’t see how the stats are likely to get any better.

It’s 4 in the morning here. I’m blown away by this post. Thanks, Paul, for being a mad man! This is awesome. I’ll read the comments tomorrow. Night all!

And again, a three-year average with wildly divergent numbers just obscures the problem. That’s simple statistics.
And again, mischaracterizing larger sample sizes as obscuring a “problem” is ludicrous. The problem in the first place is small sample sizes. So, yes, larger sample sizes do obscure wild swings in smaller sample sizes. Time to throw out every statistic and start over with ones that … what? Smooth out performance variation in real time by accurately predicting what a player will do over the long term? The name has changed, but we’re obviously still being Robbed blind.

“In reality, variaton is mostly a problem of sample size. How many balls does a defender get to over the course of a season? ”
I agree with this thought completely. The problem is what you call a sample. Across seasons strains the definition.
“Do we throw out OPS because what it measured in the first 50 games differed wildly from the next 50?”
The problem is that a season is an encapsulated unit – same field, same pitchers, same teammates, etc. Subsequent years are not. So much changes from year-to-year with defense, to say nothing of three years, then you can’t just assume an average is the best approximation. It’s clearly not. You’re averaging apples and oranges and calling it watermelon.
” But I’m not going to write a disclaimer every time I use WAR or UZR because this audience seems pretty knowledgeable about the strengths and weaknesses of those statistics.”
No one here that I’ve read is asking you to. The common thread seems to be about making definitive judgments or even ratings based on these faulty numbers. Go nuts on offense if you’d like. There most are confident in the results – they’re as good as we’re likely to ever have. But WAR and UZR are so variable past the top few players, then when you get to rankings, #5 could just as easily be #15 the following year. That’s the very definition of unreliable.
“As I said earlier, if the data don’t jive with what your eyes tell you, check them both out and see which makes more sense.”
Seriously, how does that approach help with Ellsbury or Jeter? I was shocked Ellsbury was so bad last year and amazed that Jeter was so good. So I should simply trust the numbers cause I’m surprised? That seems off.
Honest question: What’s the R-squared for UZR from year to year?
I’m going to guess .3 ignoring how a small number of players could be carrying that moderate correlation.
Now what the year-to-year correlation of the number of errors? That seems much more consistent to me. And yet I know that’s a very faulty stat.

That’s weird. My link didn’t post. Here’s another try.
How reliable is UZR?
I can’t believe I nailed it! A .36 for infielders isn’t horrible but it also leave 64% of the variance to be described by other factors. Outfield defense is getting to be almost unreliable since that correlation is probably carried by a small number of players.
As for wOBA – .53 isn’t that great considering how much data there is to work with.

You and I are going to get along nicely, Andrew. I agree with everything you say. Do you post any where else? I could swear I’ve seen your handle before. RAB, maybe?

positioning, types of pitchers you’re playing behind, range of fellow defensemen (and these can all have an affect on each other)
UZR actually does account for positioning and maybe I’m misunderstanding you, but the type of pitcher might affect the number and type of balls that come at you, but ultimately you’re judged against your ability to make each individual play.
As for UZR’s reliability from year to year:
more than 50 chances in both years = r^2 of .15
more than 100 chances in both years = r^2 of .19
more than 150 chances in both years = r^2 of .24
more than 200 chances in both years = r^2 of .28
Quite simply, the more of a fielding sample we have for a particular player, the great the correlation from year to year.
For comparisons sake, if we look at wOBA from 2008 to 2009 you get this:
more than 300 PA in both years = r^2 of .24
more than 500 PA in both years = r^2 of .30
So the lesson is, when there’s not a lot of UZR data on a player, there will be a lot of noise, but as the sample size increases, the data (at least from 2008 to 2009) actually becomes almost as highly correlated year to year as the stats that are considered to be the most reliable.
In the comments, Colin Wyers, who did the THT study to which Rob Paul links, says they are on the same page, and that his study actually found greater year-to-year correlation than Appelman’s did.
The comments are also instructive: Tom Tango agrees that UZR is no less variable than wOBA given a large enough sample size (he says 100 games is large enough to provide equal weight between performance and mean regression). Another commenter said he did a similar analysis and found UZR to be a better predictor of itself in the subsequent season than OPS. Lee Panas notes that UZR is actually less variable than ERA, and concludes: I think if there is concern that UZR is not reliable, then there should be similar or greater concern about common pitching stats.
Bottom line; UZR varies, sometimes widely. So does every other statistic. There is nothing in that variation to cause us to doubt UZR’s usefulness as a statistical tool. Its No. 1 flaw is that it relies on subjective interpretation in obtaining its data. But that still makes it more reliable than me — or anyone else — using my/their subjective interpretation of what I/they see, trying to remember it all at the end of the year and saying, “I/We think he’s a good fielder.”

A correlation of .30, at best by your numbers, leaves 70% of defense to be explained. Good luck with that.
Tango citing the best and worst hurts his case. They’re not the problem. It’s the other 80% that need explaining if you wish to do accurate rankings. You do, don’t you?
I asked it earlier: What’s the variation on WAR based on Teixeira’s best and worse defense?

“UZR is as volatile a metric as FIP and wOBA.”
I’m not sure I buy that. Pitching maybe, but I don’t understand wOBA enough to think it through. Care to explain what goes into wOBA? Does it use BABIP?
“there’s really no reason to have a great deal of confidence in UZR/WAR, particularly on two-year samples or larger.”
Sweet, then we agree.
Who’s Rob?

That’s an excellent point, Andrew. It’s varying within the season too. I would gladly support a UZR or FRAA or +/- leaderboard. But really all you’re doing is posting a number like any other. At the end of the year there’s just not going to be much said of the following year. Or more accurately, about 30% will be said. Can we improve that a bit with the cameras? Hopefully.
Of course I wish Jeter were a fantastic shortstop. But I can see with my own eyes that he’s solid but lacks range. He’s always been that way too.

“…But that still makes it more reliable than me — or anyone else — using my/their subjective interpretation of what I/they see, trying to remember it all at the end of the year and saying, “I/We think he’s a good fielder.”…”
good point paul…i’ve said it before, you’re making a believer out of me that stats beyond the ones relied on traditionally have value in assessing performance…as long as we understand and respect the inherent flaws in such data and systems used to churn that data [and you seem to]…i’m still a little old school in that i prefer to temper my reliance on pure stats with anecdotal evidence, and stuff that i see with my own two eyes, bad memory and all…i have to admit a little favoritism creeps in to distort things…jump throws, the face dive, the weird jeremy giambi play, and being a yankee, that all makes jeter better than average in my mind…and i’d take tex over any other 1b despite his #15 ranking…ask the yankee infielders how many times tex saved them a throwing error…and good post…my impression was that you were merely trying to counter conlin’s over the top proclamation by offering up another way of looking at it…nothing wrong with that, but i knew he was wrong without looking at the stats ;) …

I don’t agree with the statement that defensive stats are notoriously flaky but better than anecdotal evidence and I think that statement sums up well the difference in perspectives between, for instance, Paul and Krueg – or at least much of the difference.
At a certain point of “flakiness” a stat becomes much more misleading, less worthwhile, and certainly less interesting to debate (to me) than anecdotal evidence because at least the latter is explicitly subjective.
If you tell me Nomar was better than Jeter because of a whole range of things you saw Nomar do on the field that you thought Jeter didn’t do as well when you watched him, we can have a fun debate about the performance of players we’ve followed for years – recalling games we watched and reliving the emotion we felt while being fans at a game or sitting someplace and watching on TV. This is much of the fun of fan-debates when those discusions can be kept civil or even playfully argumentative. Beyond the fun, are these methods of gauging a player’s value or performance all that accurate? No, but I think most fans would acknowledge that they pale in comparison to RELIABLE stats when such stats exist for the particular area of performance that is being debated. And I certainly don’t think that eyewitness accounting is completely useless in gauging a player’s performance.
On the other hand, a stat that is so flaky as to posit, for instance, that Kevin Youkilis was more than three times better at defensing first base than any other player in the league, (or frankly that any Yankee is that much better at any aspect of the sport than all other players in the league at his position) is both obviously misleading and much more annoying to argue because it is masked as not only objective but somewhat accurate because it is – after all – a number. Come to think of it, is there any other stat which is viewed as even moderately reliable that would rate any player’s performance at more than triple the value of the next best performance in that category? That’s not meant as a rhetorical quesiton to prove a point – I am actually curious if there is one because I can’t think of one. If there isn’t then it does further cast doubt for me on the value of single-season UZR, on which i didn’t really need any more doubt to be cast frankly.
It seems to me at the very least to be arguable which measure (the exremely flaky stat or the unreliable eyewitness subjectivity) is more accurate as a measure of a player’s performance. And it’s very clear to me which I’d rather debate if those are the only two measures available to me for certain kinds of performance on the field.

I greatly appreciate the last two comments here since although Im a huge fan of baseball statistics and respect their use in talking about baseball, I feel that sometimes they are indeed relied on a bit to heavily. I do hope these well articulated arguments by IH and YF will be remembered when people disagree over statistical arguments. Thanks guys…

Sigh.
If you’re unwilling to believe in the veracity of the statistic — or any statistic? — I can’t do much about that. When the greatest statistical minds in the genre run studies that show that UZR correlates better year-to-year than ERA, then I’d be curious as to what statistics you’re willing to accept.
Batting average is, on the face of it, a ridiculous stat: The denominator is all plate appearances — except a lot of those that end in a positive result (BB or HBP) as well as a handful that result in a negative result with some positive side effects (SF). Say what?
OPS/OPS+ is a well used stat that has a lot of value, but it doesn’t weight on-base percentage properly, yet we all use it to determine the value of players.
ERA/ERA+ fails entirely to account for bad luck/defense, something over which pitchers have absolutely no control.
Wins are practically worthless, yet many people still look at them as the ultimate arbiter of pitching value.
So if you’re unwilling to accept a statistic that has flaws — as basically all of them do — but still gives a mostly accurate view of defensive prowess, again, I can’t do anything about that. But then I would expect you would treat all statistics with such skepticism, and then I would ask you: How do you evaluate players without being able to see all of them play every game?
a stat that is so flaky as to posit, for instance, that Kevin Youkilis was more than three times better at defensing first base than any other player in the league,
Well, in 1919, Babe Ruth hit more home runs than most other teams. I guess we need to throw out home runs as a stat? Ok, that’s not fair to your point, but you’re not being fair to mine, either. I explicitly said that Youkilis’ number is being affected by small sample size, something that afflicts all statistics. It certainly affects OPS (which I assume you’re OK with). Get a 50-60-game sample, and see what that does to the leaderboard of any statistic.
Meanwhile, it feels like you didn’t bother taking the time to read any of the defenses of UZR that I posted if your principal concern with the stat is something I already acknowledged and addressed in the original post.
they pick a little of this (ops) and a bit more of that (obp), weight these with a score of other factors, and at every turn they’re subject to error, and also leaving something out. in aggregate, they might be the best measures we have, and fairly accurate.
So they’re the best we have, and they’re fairly accurate, and that’s a reason for … what, exactly? I guess I don’t understand the point, notwithstanding there’s no overall-value stat that actually includes either OPS or OBP, as far as I know. (But I know you were just throwing stuff out as an example, not looking at one particular statistic).
I get very little opportunity to watch any baseball during the regular season. I listen to a bit more via XM. That’s it. If all I have to determine which players are the best are “the best measures we have, and fairly accurate,” then I’m going to use them. If others have anecdotal evidence that something is askew, by all means, it can be presented — but no one has yet explained how anecdotal evidence, which has led as a quick example to HOF arguments for Jim Rice (“the fear”) and Jack Morris (“pitching to the score”), is superior to these metrics.

The only problem with fielding metrics is they lack charisma. Otherwise, I’d guess they do a better job than the eyes in evaluating a player’s contributions on the field. It’s a little odd to me that people form opinions, even strong ones, about players’ fielding abilities based on the games they watch. I think most of us watch the games on tv. Television doesn’t allow us to see fielding, especially the most important part of fielding–the range of the player. We are hardly ever privy to where the fielder began and finished during a fielding sequence. He is hidden from view. Even instant replays fail to show us much without the context of when the ball was hit. There are, of course, outliers: players like Ozzie Smith, who are so brilliant that your eyes cannot deceive. There are players who are so bad, you don’t need the fielding metrics to know. But the majority of the time, I think it’s very difficult to come up with an accurate view of a player as a fielder based on watching the games on tv.

It doesn’t take a genius nor an experienced eye to see that Mark Teixeira is one of the best, if not the best, defensive first baseman in the AL. The stat that Paul provided that I questioned had him as the 15th best…sooooooooooo anyone else agree with that statistic being true or reliable?

The two phrases “…if you’re unwilling to accept a statistic that has flaws…” and “If you’re unwilling to believe in the veracity of the statistic — or any statistic?” and the 6 paragraphs of your response that those two phrases frame make up a large red herring in my humble opinion.
I am not asking that you throw out all those stats or even that you throw out UZR. I am asking that you not discount anecdotal evidence (or comments based on common sense) with what Krueg read early on in the thread as smugness – a perception I shared then and which I perceive again frankly with the patronizing “sigh” that begins your response to me (what is that anyway — am I supposed to apologize for forcing you to deign to respond to me?)
All I am asking for – which I understood at least a couple of other regulars here to support – is for you to be willing to engage with (or at least not to dimsiss out of hand) discussions of a player’s performance that reference anecdotal evidence and especially when they are offered in response to the flakiest of statistics.
SF and you have both noted in your comments here that you did indeed welcome such commentary, though in the post you wrote “Defensive stats are notoriously flaky, especially on one-year samples, but it’s better than anecdotal evidence” which is the phrase with which I took issue in my comment. In that comment I did not argue that anecdotal evidence is superior to statistical measures in gauging a player’s value (and certainly not in ranking players against each other which would, as you and Nick say, require watching a ton of games with a great deal of insight, perceptivity, and knowledge of the game). But I did argue that – both as a source of fun debate and as a gauge for talent that is certainly more unreliable than many stats but arguably not for the flakiest of them – anecdotal evidence should be valued as well.
Einstein said “not everything that can be counted counts and not everything that counts can be counted” – and that’s ultimately my point both on this thread and for the argumentation we have on this site generally. It is not meant to discount statistical arguments – not at all. It is simply meant to put a stake in the ground for the value of also gauging players’ worth and value by observing the game. (Aside: it always helps to situate yourself with a Nobel Prize winning physicist when arguing with someone who is better with numbers than you are)
As for the impression that SF picked up that I somehow discounted all the hard work you did with this post, nothing could be further from my intent. Seriously. I find your posts consistently fascinating, thought-provoking, and challenging. They make me wish you were a Yankee fan (to which end I pray for your soul). I don’t like the dismissal of non-stat based analysis and opinion that I sometimes feel accompanies them, but that is a rather minor point relative to the value I get out of reading them and if it is the case that I am the only one who reads some of them that way then it is my issue to deal with, not yours.
By the way, in 1919 when Ruth hit his 29 HRs, there were 5 other players who hit more than one-third of that total, so quite apart from that example being unfair to my argument as you graciously note, it is actually not a true counterpoint to it. So yeah, we can keep that stat…

“It doesn’t take a genius nor an experienced eye to see that Mark Teixeira is one of the best, if not the best, defensive first baseman in the AL. The stat that Paul provided that I questioned had him as the 15th best…sooooooooooo anyone else agree with that statistic being true or reliable?”
It’s funny. The aesthetics of his fielding don’t appeal at all to me and don’t suggest an elite fielder. That doesn’t mean he isn’t. But since Donny Baseball and Keith Hernandez are my fielding heroes at that position, I associate thin and smaller body types as the ideal at that position. It’s not a particularly rational way of judging fielding.
Anyway, Paul, in this thread, posted a Tom Tango response to the Mark Teixeira issue above. It’s an admission on the part of Tango that UZR sometimes misses some. Overall, however, he believes that UZR adds a good deal of value to our understanding of the game. I’m not sure if that satisfies the detractors of the stat, but there it is. Having no background in these things and basically feeling more and more alienated from advanced metrics this past year, it doesn’t bother me either way. I’m going to be more about embracing the drama, the frustrating waiting, the anger, the joy of the coming baseball season. I’m going to be more about the narrative and sometimes that narrative will include statistics, but it probably won’t include fielding stats.

What I’m excited by is the notion that the 2010 Red Sox will be a test – a $175 million test – on the reliability of fielding metrics on team success. If they score 800 runs but only give up 650, then they’ll have an outstanding season…

per Nick’s comments above, did you watch in person or on TV? Did you see where he started every play? Did you see the lines he took to the ball? Your eyes are valuable, without any doubt, there is no slight meant in talking about the limitations of them (or my eyes, or anyone else’s). But as has been beaten to death above the eyes sometimes lie, and they are best used as a supplement/complement to data (or rather, the data is better used to supplement/complement the eyes, since we all care more about watching than analyzing I think), even if the data doesn’t agree with the eyes. I don’t think anyone here advocates an all-or-nothing stance on anecdotal evidence or statistical data, that has never been asserted by anyone and that conclusion seems to be what we have reached through the plethora of comments.
I have no interest in picking on Teixeira – this is not about him (or Ellsbury, or anyone else on our teams) but rather it is about how data complements, defies, supplements, reinforces what we think we have seen.

I will say this: I like UZR. I think it’s useful and gives us a pretty good idea of what a fielder is doing. There are certain areas where it’s fuzzy (Catcher and First Base Defense), but I prefer it to the other systems we have.
As most fielding statisticians will tell you, you can’t really look at one year of metrics and make a definitive statement about a player – there’s too much variation.
Re: Jeter. this is the second straight year he’s been above average according to fielding metrics, after several years of being bad, indicating his improvement might be real and not a flux. In this particular case, I noticed his uptick in production coincided with the beginning of Girardi’s tenure and his repositioning in the infield. I think his improvement is attributable largely to that, and maybe a little to agility/lateral movement conditioning that he’s spoken about doing in the offseason.

“per Nick’s comments above, did you watch in person or on TV? Did you see where he started every play? Did you see the lines he took to the ball? Your eyes are valuable, without any doubt, there is no slight meant in talking about the limitations of them (or my eyes, or anyone else’s). But as has been beaten to death above the eyes sometimes lie, and they are best used as a supplement/complement to data (or rather, the data is better used to supplement/complement the eyes, since we all care more about watching than analyzing I think), even if the data doesn’t agree with the eyes. I don’t think anyone here advocates an all-or-nothing stance on anecdotal evidence or statistical data, that has never been asserted by anyone and that conclusion seems to be what we have reached through the plethora of comments.
I have no interest in picking on Teixeira – this is not about him (or Ellsbury, or anyone else on our teams) but rather it is about how data complements, defies, supplements, reinforces what we think we have seen.”
I think it’s all psychobabble. I don’t need some crazy made up stat to tell me that Tex is a great 1st baseman. Especially in light of all the scrubs we’ve thrown out there since Donnie Baseball hung up his cleats.
No, I didn’t see where he lined up every at bat, nor did I time his reactions to ground balls, etc, etc, etc, etc. What I did see, is that the guy made plays on balls I regularly saw get through our infield in the past, not to mention the crazy amount of throws he picked out of the dirt. I’ve never heard a SINGLE expert/talking head/columnist say that the guy was anything other than one of the best defensive first baseman in MLB. Period. So somehow, because of some stupid statistic that some number nerd came up with in his basement says otherwise, I’m supposed to ignore what I see with my eyes, what other fans of the game as well as the “experts” agree upon because Paul pulled some stat that said the complete opposite of conventional wisdom?

Above comment, meant to quote this from Paul in Waltham’s post: “If Jeter’s UZR can go up so dramatically because of positioning, then I’m afraid the stat is close to worthless for the purpose it’s often used in comparing players
Still, that leaves an interesting use case for teams.”
As to the team argument, that’s not really how the stats work, because the way it’s measured is to divide the field up into segments that each fielder is responsible for, regardless of positioning. So if the 3B is making plays in the SS zone, it will show up as a plus for the 3B and a minus for the SS.

Why wouldn’t positioning be considered a skill?

“Why wouldn’t positioning be considered a skill?”
How do you separate that variable from something like range? When a player moves to a new stadium and a new team, what effects do you parcel out where?
This is why I think defensive metrics will always be lacking. But I am curious enough to see how the new cameras work out. As soon as the season-to-season correlations top .50 I’ll start to take notice. But we still have a long way to go.

“How do you separate that variable from something like range?”
You don’t have to. All that matters is whether you the plays in the area designated to your position. Whether that’s down to yo your range, arm strength, familiarity with scouting reports/positioning, agility, or whatever your “toolset” is doesn’t matter in the end.

“whatever your “toolset” is doesn’t matter in the end.”
Doesn’t it matter though when making determinations about what players should be playing where? We’re seeing both the Sox and Yankees making decisions about their LF/CF. Don’t they at least want a better understanding before making a decision?

But you said it: UZR doesn’t care about positioning. It only cares about predetermined vectors that are assigned to a STATIC location on the field, no matter where the fielder actually is placed by the team’s defensive coordinator.
If this is true, it’s a horrible, horrible way to measure true defensive performance, and even further undermine’s UZR’s ultimate validity as a viable defensive statistic.
Like PFW said, hopefully the cameras will shed some light on this, and we can develop a stat that does take positioning into account, so we can get a much truer representation of a fielder’s ability. This could also greatly help defensive coordinators fine-tune their plan to maximize the team defense. So we could have a positioning-insensitive stat, which would be more useful on a team level, and a positioning-sensitive stat, which would be more useful on an individual player level.
Hell, teams probably already have this at some rudimentary level.

Just by searching “UZR positioning” on Google, I found this (bolds mine):
http://www.baseballdigestdaily.com/bullpen/index.php?option=com_content&task=view&id=79&Itemid=26
“JH: Describe the role of fielder positioning in your model and what affect it has on results.
MGL: Good question. Like most of the models and metrics out there (PMR, ZR, Dewan’s Plus/Minus System, UZR, etc.), unique (where a particular fielder likes to play or is directed to play by his coaches, or even is forced to play due to the park) fielder positioning is inherent in the results. We don’t track (no data that I am aware of does) fielder positioning before a play evolves. So really the results of UZR and all of the similar methodologies, as far as I am aware, really measure range and positioning. If one fielder is better at positioning than another, then he will likely have a better UZR even if he has the same or worse range.
For example, they say that positioning is what made Ripken so good. I don’t know, although I have seen him play quite a bit (I don’t trust my eyes very much at all when it comes to evaluating baseball player talent – at least not fielding talent).
The metric cannot separate the two (range and positioning). There is no way for us to know where a fielder is playing based on the data. Actually, I take that back. It is theoretically possible to estimate a fielder’s average position from the scatter plot of the balls fielded and not fielded, but it would be a fairly vague inference and it wouldn’t change a fielder’s UZR anyway.
Most people, myself included, feel that a fielder’s positioning, good or bad, should be part of his skill set. Of course, what if a coach misdirects where a fielder should play, or he only plays in a sub-optimal location because some other adjacent fielder is exceptionally good or bad? That fielder would unfairly get shortchanged in his UZR results. The converse is also true to some extent. If a fielder were correctly playing in an unusual location because his pitching staff has an unusual distribution of BIP’s, his fielding skill would actually be overrated. Some people have suggested that is why I have Swisher rated so good in RF.”
So you see, it’s really pretty suspect to rely on any defensive metric to know a player’s true inherent ‘range’ ability, since they cannot be separated from positioning. There can be an argument on whether or not a player is responsible for his own positioning before a play (I really don’t think so – don’t all teams coordinate their defenses to a team plan? I don’t know of any player that decides his own positioning plan, or any team for that matter that simply lets its players do whatever. Well, maybe the Mets.), but what cannot be argued is that any defensive statistic today simply doesn’t have the ability to judge a player’s actual range.

Correct me if Im wrong but UZR also doesnt take into account many of the throws a player makes (or avoids making if not confident in his arm) in the course of a season.
To just discuss this factually, UZR does take into account a player’s arm, at least UZR as calculated on Fangraphs does.
Further, here is a list from the link I posted above of what UZR does factor in its calculations:
– the location of the batted ball,
– the trajectory of the batted ball,
– the speed of the batted ball,
– whether the batter was LH or RH,
– whether the pitcher has a tendency to give up FB or not,
– what park the player is in,
– the base/out situation
It’s odd that we’re discussing Jeter, given that, until this conversation, he was a case in which everything I’d heard and seen anecdotally — range is much better than the years when he was winning those much-derided Gold Gloves — was confirmed by UZR and the other defensive stats, which all show a stark improvement from well below average to average or slightly above. I’ve heard much less grousing about Jeter’s recent GG because everyone — both anecdotally AND statistically — seems to agree that he actually has transformed himself into a competent defender. Meanwhile, YFSF has linked to articles in which the Yankee front office spoke to Jeter about his defense, and in which Jeter has said he worked on it hard for basically the first time in his life (big-time paraphrase there).

http://www.northjersey.com/sports/pro_sports/baseball/yankees/032210_Klapisch_Computer_shows_no_love_for_Mark_Teixeiras_glove_.html