Washington Nationals: Adam Dunn, UZR and Defensive Value
Given the recent spirited debates regarding Adam Dunn's defensive value to the Nats (see here and here) I thought it would be a good time to review Ultimate Zone Rating (UZR). What are it's strengths and weaknesses, and how should we use it? I know these posts are hard to find after a week or two, so I've also posted this as a permanent page at Natstats here.
Ultimate Zone Rating
From baseball’s earliest days, managers, players, reporters and fans have all tried to answer a seemingly simple question: What value does a player contribute to his team defensively? For the first 100 or so years, we relied on nothing more than fielding percentage – (balls played – errors)/(balls played). We all understand that this isn’t a good measure of value. A 50 year old man who plays third base, only fields the slowest of ground balls, makes a lazy but accurate lollipop throw to first, has a fielding percentage of 1.000. Ryan Zimmerman, who dives for balls in the camera well and makes throws from the left field tarp, will have a less than perfect fielding percentage. Still, every team in baseball would be happy to have Zimmerman at third.
History
Bill James tried to improve on the fielding percentage stat when he created Range Factor (put outs + assists)/(games played). This was a better stat than fielding percentage, but still had room for improvement. In 2003 Mitchel Lichtman (or MGL) introduced a new stat at the Baseball Think Factory called Ultimate Zone Rating (UZR). MGL tried to account for external factors such as variance in pitching, variances in ball-parks, and luck. He also converted from a games played stat to an innings played stat. In theory, UZR measures how well a player converts a batted ball into an out. This is a positional stat. You can’t compare the UZR of a right fielder to the UZR of a shortstop (the old apples and oranges thing).
How Is UZR Computed?
The field is segmented into 78 zones – 64 of which are used in UZR calculations. Every play is entered into a huge database with items such as the zone number where the ball landed, type of hit (Ground Ball, Fly Ball, Line Drive, Pop Up), etc. Here’s a chart of the zone:
To adjust for ball park effects, outfield foul balls are ignored. Also, infield line drives, which are more the result of positioning than skill, are ignored, as are infield pop-flies. Pitchers and catchers are not included in UZR.
A Little Bit of Math
After every play is entered, we start with the math. Algorithms are run for every zone, determining the number of balls hit, the type of hit, what percentage of time the ball was fielded for an out, what percentage of time the ball was fielded by position etc. For example, consider a zone between shortstop and third base. For simplicity sake, say there were 250 balls that landed in the zone. 50 landed for hits, 150 were fielded by the third baseman for outs, and 50 were fielded by the shortstop for outs. The MLB expected average would be computed for that zone, and stored in an expectancy matrix. Then, each player is compared for his position against the matrix. Now, our 50 year old man who records 10 outs in 250 chances in that zone is compared against the expectancy matrix of 150 outs, and receives a -140 for that zone. Zimmerman, who might record 190 outs in that zone, gets a +40. These computations are made for each zone of responsibility on a positional basis (the apples and oranges thing again), to create each player’s UZR. The UZR/150 you see on Fangraphs also makes adjustments for handedness of the pitcher and batter, the game state (number of outs/runner position will determine where a throw is made), double plays turned, batted ball speed, and errors made. The 150 on UZR/150 means that Fangraphs has normalized UZR calculations so that all players are compared over a 150 game season (more on this later).
How Reliable is UZR?
How Many Games Do We Need?
Tom Tango, co-author of Inside the Book, believes that 200 Plate Appearances (PA) equals 400 Balls in Play (BIP). He has also found that different defensive positions receive a different number of chances in a game. His research shows that SS and 2B get on average 5 BIP per 9 innings, 3B and CF get 4 BIP/9 Innings, and LF, RF, and 1B get 3 BIP per nine innings. Think about that. If Adam Dunn plays 150 games at 1B for the Nats this year, he will only see 450 BIP, or the equivalent of 225 PA. We would never judge a player’s offensive abilities on 225 PAs. We shouldn’t judge a player’s defensive abilities on 450 BIP. In reality, our defensive statistics sample size doesn’t reach critical mass until roughly 3 seasons of data have been entered.
UZR/150
We talked about how Fangraphs normalizes UZR data to a 150 game season. Now that we know we need 3 full seasons (or 450 games) worth of defensive stats to have a reliable sample size, we can see how unreliable this stat really is. If a player has played a half season (75 games) at a position, this is only 1/6th of the data we need for reliable analysis. Extrapolating these 75 games to 150 is no different from extrapolating 10 coin flips to a million. We can create a fancy formula to come up with a number, but there isn’t enough data to make the number meaningful.
What To Do?
Much like we use the slash stats (AVG/OBP/SLG) in tandem to get a more complete look at a player’s offensive abilities, there are multiple stats that try to measure a player’s defensive ability. In addition to fielding percentage, zone rating and UZR, John Dewan devised a stat called Plus/Minus. (For more information, go here). Plus/Minus breaks the field into zones, and is very similar to UZR. One of the biggest improvements is applied to the 1B position. UZR does not account for a 1B holding a runner. So, teams whose pitchers have a higher number of base runners have 1B susceptible to a lower UZR. Plus/Minus corrects that omission by adding "runner on 1st" as one of the game state adjustments. Of course, we still need 3 years of stats for Plus/Minus to achieve the desired level of confidence.
The bottom line is this – none of these stats paint a perfect picture of a player’s true defensive value. UZR and Plus/Minus are better than fielding percentage. Maybe we should start a new defensive slash stat called Fielding Percentage/UZR/Plus-Minus?
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The Most Important Part:
UZR quantifies defense with the same units, runs, as offense. This allows us to compare offensive and defensive contributions side-by-side. We can see that Adam Dunn was worth 35 batting runs last season and also -36 fielding runs. There is more to the system as Dunn did have a positive value with positional adjustment and replacement, but the big thing is being able to compare offense to defense.
UZR may not be a perfect measure of defense but it does show us that defense can be tremendously important.
We may know a guy is a “bad defender” but by quantifying that ability in runs we can now say how important it is that he is “bad”
Well to say you have to have 3 years of data shows implies a simplistic understranding of stats
What degree of confidence is 3 years? 99%? On the other had,, a year should give you some solid degree of confidence and a likely range for the stat. I have never crunched those numbers, but I’ll bet 1 year is a 90% confidence level. That is still fairly confident. But even if its 75% it still gives you a some idea of the true mean (talent level). Someone with a UZR/150 of -25 after 1/3 of a season has low odds of finishing 0 in 1 year or even 3. Sure it is possible he had real real bad luck while playing the hot corner and the talent level is much higher, but it is less likely than being accurate. In other words, a year gives you a fair degree of confidence, just not very high degree of confidence.
I have read a handful of scholarly papers in the top journals with sample sizes of less than 10 (in finance). Yep less than 10 total points of data. You get a low confidence level (like 65%), but they are far from useless. Having a small sample size does not mean it does not give you some idea of the true results. It is simply less clear than a much larger sample.
So in no way can you say UZR/150 is useless with only 1 season or even 1/3 of a season or even 1/10th of a season. You simply are less confident in those results being the true mean. It still gives you some hint at the true mean.
"What you know is often the enemy of what you can learn" Bill James
I find it funny that you directly attack the people who say that you need 3 years of a sample
as ‘not understanding stats’ when you routinely incorrectly interperet stats, both here and on fangraphs. I’m sorry, and maybe this is just a bad week for me, but i’m really kind of tired of posts like this from you, Brian.
I know that you blindly follow whatever Dave Cameron writes down, but I think that learning to think for yourself would do you a world of good. Investigate why the numbers are the way they are, don’t just accept them.
You saw it yourself, Adam Dunn has had less than a full season of games at first in his career.. How is that not a small sample? You are then posting sample sizes of 500 innings??? Do you have any idea how small of a sample size 500 innings is on defense?
Also, your analogy of " I have read in scholoarly journals"… does not qualify as proof of anything… because
A. We have no idea what they were studying, or how much data they had collected… without knowing any of the particulars on a said study, the information you provided is beyond useless to us.
B. You tell us this information and basically say “trust me guys.” Sorry, dosen’t work like that.
If you think that a UZR/150 for 1/10 of a season is not meaningless, than once again i’m sorry but, you have no idea how to interperet sample size data as it pertains to major league baseball. Nothing can be assertained from a guy playing 16 innings at a position. If you don’t know that, you need to go do some homework.
Also, find me an article that says that you can rely on one year of UZR/150 for first base with 95% confidence… I highly doubt you will find one
I saw one of your posts at fangraphs where you intimated that you didn’t like that Dunn “thought of himself as a hall of famer” as you put it, so maybe that’s where some of the bias comes in.
Stop misrepresenting things, blantantly or otherwise… It is annoying, and insulting to our collective intelligence.
I have read that one years of data has a range of +/- 10
with 95% confidence. Dave Appleman said it as has dave cameron in the past.
if that is true then someone like Dunn who has played 155 complete games at first with a -17 UZR/150 actually has a 95% chance his true talent level over those games was -7 to -27. Since some of those stats were accumulated when he was clearly younger, and typical players over the age of 27 tend to show tiny declines in their range every year thereafter, common sense says it is more likely his talent level is worse than better than that range.
For some reference: here are the games DHs that have played some first base in the their careers.
Ortiz has 232 games worth of UZR data as a firstbasemen and his UZR/150 is -3.5 for his career. Thome’s got 570 or so games and is -2. Dimitri Young has about 450 games of data at first with a UZR/150 in his career as -4. Michael Cuddyer has 64 games of data for his career at first and is -1.4. Giambi has 1211 games worth of data at first and is -7 for his career. Mike jacobs has 384 games of data at first and is -9.0 for his career.
These are some of the games worst first base defenders by far and they are all by UZR/150 measures outside Dunn’s career range of -7 to -17 with 95% confidence. it is very fair to say Dunn has been just about the worst first base defender in the game over his career with a very high confidence.
note: 32 players played at least 500 innings at firstbase last season only Ishikawa at +19.1, Youklis at +15.2, Kotchman at +11.1, and Dunn at -25 had UZR/150s outside of the range +10 to -10.
Dunn is a bad first basemen. it is fair to say he is very likely the worst in the game and it is not close. the stats back that up strongly. If you do not agree than take it up with fangraphs they have had several articles saying the same thing.
"What you know is often the enemy of what you can learn" Bill James
"If you do not agree than take it up with fangraphs"
Excuse me? I’m sorry, I must have missed the ruling which dictated FanGraphs as the ultimate arbiter of anything.
My problem, by the way, is not with them, but with your gross overstatement of the value of certain stats (while seemingly with no sense of irony dismissing those same stats when they don’t jibe with your preconceptions), and, worse, your jaw-dropping misuse of statistics. For someone who purports to be a budding PhD in econometrics, your cavalier (and often flat wrong) statistical “calculations” don’t serve your credibility at all.
Rob
"Man may penetrate the outer reaches of the universe, he may solve the very secret of eternity itself, but for me, the ultimate human experience is to witness the flawless execution of a hit-and-run." -- Branch Rickey
I have never crunched those numbers but I bet... 90%
so basically a number you just pulled from the sky. You expect us to accept this as a valid opinion? why?
Dunn produces nice numbers at times but he is constantly hitting
a big HR followed up with numerous bad weeks which end up costing us much-needed runs
He is someone we should be glad to have NOW but as we get better, he should be phased out
Phased out as in this season? With a free agent for next year? Or in the next two when Marrero's ready?
Vivian Jaffe: "Have you ever transcended space and time?"
Albert Markovski: "Yes. No. Uh, time, not space... No, I don't know what you're talking about."
by Patrick Reddington on Mar 27, 2010 10:23 PM EDT up reply actions
I'll stick with Tom Tango
He has invented a pile of modern stats and gets paid by pro teams to build custom algorithms. Got to respect the bigger dog…
Relax, all right? Don't try to strike everybody out. Strikeouts are boring! Besides that, they're fascist. Throw some ground balls - it's more democratic.
by natsstats on Mar 27, 2010 10:42 PM EDT via mobile reply actions
UZR adjustments
“UZR does not account for a 1B holding a runner. So, teams whose pitchers have a higher number of base runners have 1B susceptible to a lower UZR.”
Sure it does. UZR adjusts for outs and baserunners so a runner on first and no one on second (where the runner is held by the first baseman) is treated separately.
MGL
UZR
Two more things in response to a comment above: One, first base is the only position where we don’t see an aging decline from the get go. Two, there is not a symmetrical confidence interval around a sample UZR like -7 to -27, because a skill like defense is typically normally distributed, or at last part of a normal curve. A traditional confidence interval (which is symmetrical) assumes that all values above and below the midpoint are equally likely. If that were true, we would not regress the sample number (-17 for Dunn) towards zero (or some mean which represents the population the player comes from).
MGL

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