F/X VisualizationsApril 10, 2009
Checking in on Seattle's New Outfield
By Dave Allen

With about half a week's worth of games played I wanted to check in on a major story from the offseason: the increasing importance teams put on defense when acquiring players. We saw some all-hit no-glove guys get much smaller contracts than expected and we saw the Seattle Mariners trade for Franklin Gutierrez and Endy Chavez, two defensive standouts not know for their offense, and promptly make them two thirds of their starting outfield. The outfield hasn't reached its full defensive glory yet because Ichiro is the DL for a couple more days. But the first couple days the Ms still started a pretty good outfield with Gutierrez and Chavez every game and the third spot given to one of Ken Griffey Jr., Wladimir Balentien and Ronny Cedeno.

Their play has already received rave reveiws from Ms fans, so I wanted to see just how good it has been. Small sample size be damned, I thought I would check it out.

Again I am using Peter Jensen's Gameday defense metric as my guide (and his invaluable translation factors as my tool). In this case I took all balls in play at the Metrodome (from 2005 to 2008) and looked at the out percentage (1-BABIP) by location, those are the colors in the image. Over that I plotted all the non-homerun fly balls and line drives that Seattle's outfield saw in their first series, the filled circles are hits and the open outs. Now you can compare how Seattle's outfield did versus the average outfield at the Metrodome. A filled circle in the middle of blue is a hit in a location that most outfields turn into an out, and an open circle in yellow/red is an out which most outfields would let drop in for a hit.


The Mariner's outfield looks pretty good. A couple hits in the blue/green region (one of those in right is Griffey's fault) but a ton of outs in the yellow/green region. As a quick check I added up the expected number of outs and compared that to the number the Mariners actually made. There have been 40 balls in play to Seattle's outfield so far and the average outfield makes 21.75 outs. The Mariners made 25 outs. They are 3.25 outs above average just four games into the season (how many over Raul?).

Huge caveats apply here. 1) Jensen's translation factors that let you go from Gameday's pixel to feet sometimes change year to year and I am using the 2008 numbers for the 2009 hits. So the location of the hits could be off by a couple of feet. 2) Gameday records where the ball is fielded not where it lands, which would be more important. 3) This should be in no way viewed as a substitute for or peer of the real fielding metrics. Once they come out you can ignore these results.


That is a really great way to visualize the field of play. Is there an easy way for us to get more of these color coded diagrams for the other parks?


I am glad that you like them. Next week I am going to do a longer post on this idea of locational out% (or locational BABIP), and I might post more of the images. I will think about if it is feasible for me to post all of them.

Awesome. Even if you decide not to post them all, maybe you could email them to me? I understand the imperfect nature of some of this data (as described in Jensen's article), so most conclusions should be taken with grains of salt. But even still, have you thought about comparing locational out% data for the home outfielder against the aggregate "visiting outfielder" data? This methodology would be a pretty flawed way of comparing outfielder range (only half a season's worth of outs instead of the 2-3 full seasons that some argue is necessary for a representative defensive sample; the unbalanced schedule means 2006 NL East shortstops get compared to Hanley ~3 times more often then they get compared to Adam Everett), but I still think it would be pretty interesting comparison. Cool stuff. I can't imagine how convoluded the data is going to look for Fenway's left field...


that is a really cool idea as a way to look at home/away fielding splits. I will give it some thought. Here is fenway's fielding map:



Great work. I've got a quick question for you that you may have answered elsewereh. Apologies in advance if you have.

I'm wondering how you calculate the continuous run values both for these graphs and the graphs of the strike zone. The work I've seen previously works out a value for a series of different bins but you seem to have interpolated between the various strikes/landing points.

Did you fit a continuous function across all the points - in which case what curve fitting function are you using?


I like it. Could you check up on the Seattle outfielders when the sample size is large enough? I can't wait to see what happens.


The underlying data is actually discrete. Like others I also bin the data, but just use more bins. Then I use routine in the statistical package R, which creates the 'smoothed' images from the average of each bin. All of the mathematical heavy lifting is done behind in the scenes in R, the command I use is filled.contour.


Yeah I think that I will be checking in on Seattle's outfield later in the season, and maybe Baltimore's too since they could have very good outfield defense when they play Jones, Markakis and Pie. But, as I said in the post, these numbers should be taken with a grain of salt compared to the more sophisticated fielding metrics. Fangraphs has UZR (I think it is updated weekly during the season) and the hardball times has RZR and OOZ (updated frequently in season as well). Those are great places to check in on team and individual fielding performance over the course of the season.