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Nice piece, Jeremy. Question: have you ever looked at K rate (or whiff %) in terms of release point? For example, it might by that the further from center of the rubber a pitch is released by a RHP, the higher the whiff rate will be for RHH (and perhaps the reverse for LHH), controlling for velocity and movement.
It's not clear to me that a -14% finding for hitters and a +13% finding for starting pitchers (or +11% for all pitchers) suggests a lack of symmetry for replacement-level. Seems pretty close given the limitations of the methodology. And a crucial difference is the ability to assign playing time more efficiently among pitchers. Let's say each expansion team has an average of 2 above-replacement hitters and 2 above-replacement pitchers. The hitters might account for 20% of the team's PA. But two so-so starting pitchers could account for 30% of opposing hitter PAs. So assuming these teams are not truly 100% replacement players, I'd expect the pitching to look a little less bad.
You also have a potential survivor bias at work here. Expansion teams get to throw a lot of guys out there and see who succeeds. The expansion pool includes a few better-than-replacement players, and these will then get a disproportionate amount of playing time. So these team performances will be skewed upward, although that presumably affects hitting and pitching equally.
Colin: Can you give us Zimmerman's rating at 3B?
Yes, it is just a hypothesis. But really it doesn't matter: what we want to compare is the expected outs on BIP each "engine" generates. I know Fangraphs posts UZR Range runs, so that's easy. Is "rPM" the comparable for DRS? If those are actually quite close, then we can worry about HRs, pickoffs, arms, etc. (to the extent we care about those). But my guess is they aren't that close. And of course, that still leaves a lot of questions about bias in the underlying data.....
Studes: you did raise the issue of units above: "Plus, it's denominated in runs, which would make it different from DER." So I think Colin's reply was on point.
But different fruits is a separate issue. If both DRS and UZR include DPs and OF arms, then it seems like you're comparing salads with the same fruits. It's true that to the extent there is a difference, we won't know without digging deeper how much to attribute to each of the 3 elements:
1) expected DER
2) expected DPs (actual DPs must be same)
3) expected base advancement (outs on bases must be same)
But, I would make 2 points: 1) it seems useful to see how well the two system's total expectations or modeled reality compare, given identical data, and 2) realistically, expected DER likely accounts for the lion's share of any overall difference there is.
And "inconsistent misinterpretation?" Sounds like Dubya..... :>)
Colin: Am I interpreting you correctly that the correlation of expected DER for DRS and UZR is just .28? That does indeed seem low. On the other hand, expected DER at the team level probably have pretty low variance: most pitching staffs collectively must allow a BIP distribution pretty close to average. So it's hard to know what the correlation "should" be.
It would be interesting to know what the UZR/DRS correlation is for expected outs at the player level. One would hope that it is much higher, as the variance at the player level will be much higher.
Very nice work, Colin. Your PAA is very close to Tango's WOWY estimate (-436 thru 2008), which makes sense. A few observations:
It occurs to me the Jeter ball distribution question could largely be settled by looking at the proportion of GBs handled by NYY 1B and LF (total) over Jeter's career. If Yankee pitchers have somehow managed to avoid Jeter to a significant extent, this would have to result in a larger than usual number of GBs to the right side. It's simply unimaginable Jeter could be shortchanged on opportunities without a big skew toward the other side of the field.
One way you might try to show definitively that PBP data exaggerates opportunities for good fielders is to examine if there's a correlation between a player's minor lg fielding performance and their MLB PBP opportunities. There should be no relationship whatsoever. That would give you a much larger sample than looking only at MLB team-switchers.
The difference between UZR and DRS is interesting. One reason UZR likes Jeter so much, I think, is that it treats errors as 100% a fielder's responsibility and Jeter makes few errors. Since UZR never estimates an out probability at much over 80% on any other kind of GB, errors really increase a player's imputed opportunities (incorrectly, in my view, since there's no reason to think players who make errors actually have more easy plays). Perhaps DRS treats errors differently?
It looks like your run multiplier is about .8 runs per play. I would have guessed it's closer to .7 for a SS. Is .8 correct?
Colin: Any chance you could add a version of the chart adjusting for MLB runs/PA? That would make it easier to see how the relative rankings of the positions changes over time.
K:BB ratio is a "fun" state. But looking at the K-BB differential (K minus BBs) is a much more relevant measure of pitching performance. Clearly, Wells’ 58/4 K/BB is not in any way “better” than Schilling’s 150/11. Thinking of them as +54 and +139 provides a much better sense of their value in preventing runs. (A pitcher with a much lower strikeout rate than Wells' couldn't survive even with zero BBs.)
In fact, if you compare first half and 2nd half performance of Eric’s selected pitchers, there is no correlation between 1st half and 2nd half K/BB ratio. However, 1st half differential almost perfectly predicts 2nd half differential (r=.96), suggesting it is a far more reliable metric.