People take metrics out of context so much. UZR
Sample Size and Reliability
One thing to keep in mind is that as with all metrics based on sample data where you are trying to estimate a true mean or value, the more data you have generally the more reliable your estimate. In other words, the more opportunities that UZR is based on, the more reliable the number, everything else being equal. On defense, 2B, SS, and CF have almost twice the number of opportunities per game than do the other positions on the field, but that does not necessarily mean that a UZR based on 100 games at SS is as reliable as 200 games at 3B. There are other factors that affect the reliability of a sample number.
How many UZR opportunities do you need for UZR to be reliable? There isn’t any magic number. If I asked you how many AB you need before a player’s BA becomes reliable, you would likely answer, “I don’t know. The more the merrier I guess.” That is true with UZR and with all metrics. Of course, for some metrics, you need more or less data than for other metrics for an equivalent reliability. It depends on the sampling error and the spread in underlying talent, and other things that are inherent in that metric. Most of you are familiar with OPS, on base percentage plus slugging average. That is a very reliable metric even after one season of performance, or around 600 PA. In fact, the year-to-year correlation of OPS for full-time players, somewhat of a proxy for reliability, is almost .7. UZR, in contrast, depending on the position, has a year-to-year correlation of around .5. So a year of OPS data is roughly equivalent to a year and half to two years of UZR.
Another way to look at it is after one year, a player’s true talent UZR or what you might expect from him in the future is as close to that one-year number as it is to zero (technically, the average of a similar type player, which might not be zero). The best estimate is somewhere in between – in fact more or less the mid-point. Given that, I don’t think it is fair to say that one year of UZR data is “unreliable.” Of course, the words “reliable” or “unreliable” have no quantitative meaning. You can make of them whatever you want. Personally, no matter what size sample of data I look at, I always do a mental regression. For a one-year UZR, I mentally regress UZR halfway toward the mean, which means basically to “cut it in half” since the mean is defined more or less as zero. If you want to refine that “rule of thumb” a little, you can regress a player’s UZR (per 150 games) toward +2 for a fast player, -2 for a slow player, and zero for anyone in between. That is more true in the OF than in the IF, and more true at SS and 2B than at 3B or 1B, as you might expect. In addition, when I say “fast” or “slow,” I mean relative to the average player at that position. So, for example, if a player is fast, but only as fast as the average CF’er, and he is a CF’er, then you still want to regress his UZR to zero.
One problem that comes up with any metric when you combine years in order to increase sample size and thus reliability, is that a player’s true talent may change from one year to the next, such that you are in some sense adding apples to oranges. We generally handle that by giving more weight to recent years and less weight to more distant years. So keep that in mind when you are looking at multi-year UZR’s.
http://www.fangraphs.com/blogs/the-fangraphs-uzr-primer/
The truth is hasn't had enough of a sample to know. He has had some really bad times out there and he has some good ones. Fact of the matter is as he ages he will start to slow down. He is built like a linebacker and low to the ground. He would get destroyed in big ball parks. He can get away with it at Wrigley. We will know more after a full season this year but he is going to have issues and would be a defensive liability in any park out West. But, I have always said if the stick plays. They will find you a position.
