Rob Manfred: Run Killer

There are many “crimes against baseball” that one could charge Rob Manfred with, if one were inclined to use hyperbolic language and pretend that the commissioner had the sole authority to decide matters (I tend to neither but am guilty of seeking a more eye-catching post title):

* Attacking the best player in his sport for not going along with whatever horrible promotional scheme the commissioner had dreamed up

* Making a general mess of negotiations with the MLBPA

* Teaming up with authoritarian governments ranging from cities in Arizona to Leviathan itself to attempt to delay or prevent baseball from being played

* Claiming to be open to every harebrained scheme to reign in shifts, home runs, strikeouts, or whatever the current groupthink of the aesthetically-offended crowd finds most troublesome

From my selfish perspective as a sabermetrician, though, I will argue that the greatest crime of all is that he has rendered team runs scored and allowed totals unusable. The extra innings rule, which I doubt will ever go away even if seven-inning doubleheaders do, makes anything using actual runs scored incomparable with historical standards (in the sense of parameters of metrics rather than context). A RMSE error test of a run estimator against team runs scored? Can’t use it. Pythagenpat? Nope. Relief pitcher’s run average? Use with extreme caution.

Of course, I am not seriously suggesting that the ease with which existing metrics can be used should be a consideration in determining the rules of the game. But if you use these metrics, it is necessary to recognize that they are very much compromised by the rule.

So how can we adjust for it? I will start with a plea that the keepers of the statistical record (which in our day means sites like Baseball-Reference and Fangraphs) compile a split of runs scored and allowed in regulation and extra innings, as well as team innings pitched/batted in regulation and extra innings, and display this data prominently. Having it will allow for adjustments to be made that can at least partially correct, and more importantly increase awareness of the compromised nature of the raw data.

I want to acknowledge a deeper problem that also exists, and then not dwell on it too much even though it is quite important and renders the simple fixes I’m going to offer inaccurate. This is a problem that Tom Tango pointed out some time ago, particularly as it related to run expectancy tables – innings that are terminated due to walkoffs. In such innings, there are often significant potential runs left stranded on base, and so including these innings will understate the final number of runs one could expect. Tango corrected for this by removing these potential game-ending innings from RE calculations. It’s even more of a problem when it comes to extra innings, since rather than just being 1/18 of the half-innings of a regulation game, they represent 1/2 of the half innings of an extra inning game. This means that when we look at just extra innings, the number of potential runs lost upon termination of the game make up a significant portion of the total runs.

I gathered the 2020 data on runs scored by inning from Baseball-Reference, and divided each inning into regulation and extras. I did not, however, do this correctly, as the seven-inning doubleheader rule complicates matters. The eighth and ninth innings of a standard nine-inning game are played under very different circumstances than the eighth and ninth innings of a seven-inning doubleheader. I have ignored these games here, and treated all eighth and ninth innings as belonging to standard games, but this is a distortion. I didn’t feel like combing through box scores to dig out the real data as I’m writing this post for illustrative and not analytical purposes, but it buttresses my plea for the keepers of the data to do this. This is not solely out of my laziness (although I really don’t want to have to compile it myself), but also a recognition of the reality that many casual consumers of statistics will not even be cognizant of the problem if it is not made clear in the presentation of data.

Forging ahead despite these two serious data issues that remain unresolved (counting eighth and ninth innings of seven-inning doubleheaders as regulation innings rather than extra innings, and ignoring the potential runs lost due to walkoffs), I used the team data on runs by inning from Baseball-Reference to get totals for innings played and runs scored between regulation and extra innings. Note that these are innings played, not innings pitched, understating the true nature of the problem since almost most of the regulation innings include three outs (with the exception being bottom of the ninths terminated on walkoffs), a much greater proportion of the extra innings do not.

Still:

Expressed on the intuitive scale of runs per 9 innings, regulation innings yielded 4.80 runs, while extra innings were good for a whopping 8.40, a rate 75% higher. And no wonder, as Baseball Prospectus RE table for 2019 shows .5439 for (---, 0 out) and 1.1465 for (-x-, 0), a rate 111% higher. That we don’t see that big of a difference is due to an indeterminate amount to sample size and environmental differences (e.g. a high-leverage reliever is likely pitching in an extra inning situation, unless they have all been in the game already) but probably more significantly to the lost potential runs.

Considering all runs scored and innings, there were .5378 runs/inning or 4.84 R/9 in the majors in 2020, so even a crude calculation suggests a distortion of around 1% embedded in the raw data due to extra innings. Of course, the impact can vary significantly at the team level since the team-level proportion of extra innings will vary (1.25% of MLB innings played were extras, ranging from a low of 0.40% for Cincinnati to 3.44% for Houston).

How to correct for this? If the walkoff problem didn’t exist, I would suggest a relatively simple approach. After separating each team’s data into regulation and extra innings, calculate each team’s “pre-Manfred runs” as:

PMR = Runs in Regulation Innings + Runs in Extra Innings – park adjusted RE for (-x-,0)*Extra Innings

= Runs - park adjusted RE for (-x-,0)*Extra Innings

You could address the walkoff problem by adding in the park adjusted RE for any innings that terminated, but this gets tricky for two reasons:

1) it means that the simple data dividing runs and innings into “regulation” and “extra” is inadequate for the task; I doubt “potential runs lost at time of game termination” would ever find there way into a standard table of team offensive statistics

2) it overcorrects to the extent that the legacy statistics we have always used ignore the loss of those potential runs as well. Of course, the issue is more pronounced with extra innings as they represent a huge proportion of extra innings rather than a small one of regulation innings (and because the nature of Manfred extra innings increases the proportion of walkoffs within the subset of extra innings, since run expectancy is 111% higher at the start of a Manfred extra inning than at the start of standard inning).

Also note that when I say park-adjusted, I mean that the run expectancy would have to be park-adjusted not in order to normalize across environments, but rather to transform a neutral environment RE table to the specific park. I wouldn’t want to use “just” 1.1465 for Coors Field, but rather a higher value so that the PMR estimate can still be used in conjunction with our Coors Field park adjustment as the Rockies raw runs total would have been pre-2020. Another complication is that the standard runs park factor would likely overstate the park impact because of the issue of lost potential runs (they too would increase in expected value as the park factor increased).

The manner in which I attempted to adjust in my 2020 End of Season statistics was to restate everything for a team on a per nine inning basis, and then use the R/9 and RA/9 figures in conjunction with standard methodology. But this is also unsatisfactory – for instance, a Pythagorean estimate ceases to be an estimate of the team’s actual W%, but rather a theoretical estimate of what their W% would be if they played a full slate of nine inning games. The extra innings aren’t really a problem here, but the seven-inning doubleheaders are. As long as these accursed games exist, in order to develop a true Pythagorean estimate of team wins, one would have to estimate the exponent that would hold for a seven-inning game (Tango came up with a Pythagorean exponent of 1.57 through an empirical analysis; my theoretical approach would be to use the Enby distribution to develop theoretical W%s for seven-inning games for a representative variety of underlying team strengths in terms of runs and runs allowed per inning, then use this to determine the best Pythagenpat z value), and then use runs and runs allowed per inning rates to estimate separate W%s for seven- and nine-inning games, then weight these by the proportion of a team’s games that were scheduled of seven and nine innings.

I also took the unfortunate step of ignoring actual runs everywhere (as I mentioned in passing earlier, Manfred extra innings wreck havoc on reliever’s run averages), since the league averages are polluted by Manfred extra innings. Again, I am not advocating that sabermetric expediency drive the construction of the rules of baseball, but it is a happy coincidence that sabermetric expediency tracks in this case with aesthetic considerations. I should include a caveat about aesthetic considerations being in the eyes of the beholder, but the groupthink crowd that is now in the ascendancy rarely sees the need to do so. No surprise, as many also subscribe to the totalitarian thinking that is ascendant in the broader society. They’ll tell you all about it, and about what a terrible person you are if you dissent, for $25.19.