TL;DR Use OAA. Ignore RDA/ROS.
Baseball Prospectus came out with a new defensive metric in the vein of their DRC+ and DRA- stats. If you’re familiar with my commentary on DRC+, this is going to hit some of the same notes, but it’s still worth a quick read if you made it this far. The infield and outfield models for RDA behave extremely differently, so I’m going to discuss each one in a separate post. The outfield post is here.
The infield model is just simply bad compared to OAA/DRS. If somebody is giving you hype-job statistics and only tells you how well a team does against a non-division same-league opponent who’s at least 2 games below .500 while wearing uniforms with a secondary color hex code between #C39797 and #FFFFFF in Tuesday day games during a waxing gibbous moon.. well, that ought to make you immediately suspicious of how bad everything else is. And the same for the statistics cited in the RDA article.
That is.. the opposite of a resounding win for ROS/RDA. And it’s worse than it looks because OAA is (theoretically, and likely practically) the best at stripping out fielder positioning, while DRS and ROS will have some residual positioning information that will self-correlate to some extent. DRS also contains additional information (extra penalty for botched balls down the line, throwing errors, double plays) that likely help it self-correlate better, and ROS/RDA appear to contain outside information as described above which will also help it self-correlate better.
OAA/ inn | DRS/ inn | ROS | RDA/ inn | N | |
to OAA | 0.44 | 0.32 | 0.22 | 0.21 | 177 |
to DRS | 0.26 | 0.45 | 0.30 | 0.30 | 177 |
ROS/RDA correlating significantly better to DRS than to OAA is suggestive of a fair bit of its year-to-year self-correlation being to non-demonstrated-fielding-skill information.
Even in their supposed area of supremacy, team-switchers, infield ROS/RDA is still bad. Classifying players as either non-switchers (played both seasons for the same team only), offseason switchers (played all of year T for one team and all of year T+1 for a different team), or midseason switchers (switched teams in the middle of at least one season).
All IF | OAA/inn | DRS/inn | ROS | RDA/inn | n |
Offseason | 0.40 | 0.45 | 0.43 | 0.46 | 79 |
Midseason | 0.39 | 0.31 | 0.13 | 0.11 | 91 |
Off or Mid | 0.39 | 0.38 | 0.28 | 0.28 | 170 |
No Switch | 0.45 | 0.45 | 0.37 | 0.36 | 541 |
All | 0.44 | 0.45 | 0.36 | 0.35 | 711 |
They match OAA/DRS on offseason-switching players- likely due to overfitting their model to a small number of players- but they’re absolutely atrocious on midseason switchers, and they actually have the *biggest* overall drop in reliability between non-switchers and switchers. I don’t think there’s much more to say. Infield RDA/ROS isn’t better than OAA/DRS. It isn’t even close to equal to OAA/DRS.
Technical notes: I sourced OAA from Fangraphs because I didn’t see a convenient way to grab OAA by position from Savant without scraping individual player pages (the OAA Leaderboard .csv with a position filter doesn’t include everybody who played a position). This meant that the slightly inconvenient way of grabbing attempts from Savant wasn’t useful here because it also couldn’t split attempts by position, so I was left with innings as a denominator. Fangraphs doesn’t have a (convenient?) way to split defensive seasons between teams, while BP does split between teams on their leaderboard, so I had to combine split-team seasons and used a weighted average by innings. Innings by position match between BP and FG in 98.9% of cases and the differences are only a couple of innings here and there, nothing that should make much difference to anything.
Thanks for this – good work.
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