Two days ago, Fangraphs added the BIS +/- fielding statistics to its pages. Over the past couple days, Twitter was the scene of a conversation comparing +/- Defensive Runs Saved (DRS) to Ultimate Zone Rating (UZR), also available at Fangraphs, based on the same underlying BIS batted ball data set. The conversation was between Colin Wyers, myself, and several other contributors. Rather than let this conversation sink into the abyss of old forgotten tweets, I decided to preserve it here, with Colin’s permission.
Please consider that the following was not intended as an in-depth research presentation by any of the participants, and it was subject to the 140-character limit of the Twitter medium. I have lightly edited the transcript to improve readability.
Colin Wyers: I’m not sure what I think about this yet: http://bit.ly/aSQfXB
CW: For ’09, correlation between BIS DRS and UZR (same pbp data source) is .79. RMSE is 3.1.
CW: Should note – that RMSE is for typical player, or someone with about 66 BIZ chances as defined by BIS. Starter has ~ 300 BIZ.
CW: For players with > 1200 innings at a position, RMSE between UZR and BIS DRS is 7.5.
azruavatar: Is there anything detailing the +/- methodology?
CW: BIS periodically publishes the Fielding Bible. For difference between +/- and UZR, try this: http://bit.ly/bGC0rb
CW: Major difference between UZR and +/-, IIRC, is the baselines – UZR uses three-year baselines, +/- uses one year.
MNTwinsZealot: I understand John Dewan’s Fielding Bible +/- system, but how accurate is it? Should it be used just the same as UZR?
CW: I guess that depends on how you want to define accuracy.
CW: UZR has a higher year to year correlation with next season UZR than DRS has with next season DRS. Not sure it’s significant.
CW: UZR also seems to be a better predictor of next-season DRS than DRS is of next season UZR. Again, not sure if this is a significant result.
…Colin and I carried on a chat and email conversation, not recorded here, which led to some of the following tweets…
Mike Fast: Split into infield vs. outfield. UZR does better with outfielders, DRS better with infielders, relatively speaking.
CW: That’s interesting. I need to look at this closer.
MF: Also, I don’t find the correlation between Yr-1 error and Yr-2 error to be very high. R-squared = 0.07 (2003-09, >400 innings)
MF: Where error = DRS/inning – UZR/inning. It’s not insignificant, but less than I had expected from what you had said.
MF: UZR Yr2-v-Yr1 outfield R-squared 0.21, infield 0.19. DRS Yr2-v-Yr1 outfield 0.12, infield 0.19. (2003-2009, >400 inn).
CW: You’re normalizing by playing time, which is probably better than what I was doing. Can you look at the park switchers, too?
MF: Wow, ugly. For team switchers, UZR Yr2-v-Yr1 outfield R-squared 0.01, infield 0.06. DRS Yr2-v-Yr1 outfield 0.00, infield 0.02.
CW: That is ugly, especially once you consider that both are adjusted for park.
Robbie Griffin: I’d be interested in hearing how you feel. I saw some of your comments on the UZR vs. Dewan conversation at the Book Blog.
CW: At this point, I don’t know what these numbers mean. And I’m starting to lose confidence that what we’re measuring is defense.
CW: That last tweet probably came off as MORE optimistic than intended. I’ve been losing confidence for months – not sure I have any left.
Dan Turkenkopf: So some concerns about the quality of data that we’re basing a lot of our analysis on?
CW: Mike Fast and I have both found that the correlation for UZR year-to-year drops substantially if you look only at team switchers.
Graham MacAree: hardly a big surprise there.
CW: Combine that with my findings on the batted ball data itself (and there’s more that should be published soon), and, well…
RG: Is that for just +/- or all defensive metrics currently en vogue?
CW: You have two potential sources of discrepancy – methodology and the underlying data. At this point I have questions about both.
CW: @MacAree They’re both supposed to be park adjusted. Unless you have some other explanation…
GM: ‘supposed to be’ being the major question mark.
DT: Pitching staffs?
CW: Again, that’s SUPPOSED to be controlled for. If it isn’t, that’s a real problem.
Matt Klaassen: “and well,” what, back to range factor? FRAA?
RG: My main question would be along those lines: is it still probably better than anything else even with the issues?
CW: I don’t have good answers yet.
GM: My money is on us having a real problem. If our data is bollocksed we can’t do anything.
CW: That’s where I’m at right now as well.
GM: I don’t think I’m too disheartened by this thought – as long as the logic is sound I’m happy. Just need better data.
CW: For want of a stopwatch, the kingdom was lost.
MF: Except hope that Trackman and/or FIELDf/x some day become operational and public in some fashion.
GM: Right. As long as we’re attacking problems in the right way the source data will catch up.
CW: I think once you’ve identified the problems in the existing data, you can do more with it. We’re getting closer there.
MF: That’s a good point, Colin.
MF: Based on team-switchers, looks like outfield data is hopeless, wonder if that is mostly due to the LD counting issue you found?
MF: Team-switcher data shows UZR still has promise for infielders. What would the park/team bias be? How hard the groundballs are?
CW: There are two questions about the batted ball data – I’ve really only addressed trajectory. Location data could have issues too.
MF: Breakdown by position (sample size ~20 players) for team-switchers: UZR good for SS, 3B; mediocre for LF; useless for RF,CF,2B,1B.
MF: Breakdown by position for team-switchers: BIS +/- very good for SS; mediocre for LF; useless for RF,CF,3B,2B,1B.
MF: General insight: averaging UZR and BIS +/- does nothing to improve the year-to-year predictive power.
GM: This is for UZR/150 so pitcher staff GB rate won’t matter, yes?
CW: UZR/Inn, so that shouldn’t be a factor, right. I say shouldn’t but at this point I don’t know.
GM: Defensive innings, I imagine? so DG/9?
CW: Actual innings played, not derived innings.
CW: Can we look at year-to-year correlation for ExO in players who DON’T switch?
MF: I can’t find ExO on Fangraphs any more, is it okay to use BIZ?
CW: Hrm. Looks like they pulled DG as well. I don’t think BIZ quite gets at what I’m measuring, but it could work.
MF: Team-switchers BIZ/inn for outfielders y-t-y correlation R^2=0.06, for non-switchers R^2=0.18.
MF: Team-switchers BIZ/inn for infielders y-t-y correlation R^2=0.55, for non-switchers R^2=0.65.
MF: The difference between BIZ and ExO being ExO includes a measure of difficulty, e.g. how hard the scorer thought the ball was hit? Is that what you’re saying?
CW: Yeah. Still, I wonder how much of the BIZ correlation is pitcher tendencies and how much is scorer bias.
CW: My latest article on batted ball bias – http://bit.ly/bYycrn (This one’s free to nonsubscribers.)