The Cascading Bias of ERA

There are so many problems with ERA that it’s unbelievable. I’m not going to sit here and tell you what’s wrong with ERA, though, because you’re probably smart. But there’s a problem with ERA, and it’s a problem that transcends ERA. It’s a problem that trickles down through FIP, xFIP, SIERA, TIPS, etc. etc. name your favorite stat, etc., and it’s something I don’t see talked about much.

All of our advanced pitcher metrics are trying to predict or estimate ERA. They’re trying to figure out what a pitcher’s ERA should be, and herein lies the problem: Because they could be exactly right, but they’d still be a little incorrect due to one little assumption.

This assumption–that pitchers have no control over whether or not the fielders behind them make errors–seems easy to make. Like most assumptions, however, this one is subtly incorrect. Thankfully, the reason is pretty simple. Ground balls are pretty hard to field without making an error, and fly balls aren’t. And the difficulty gap is pretty huge.

How big? Well in 2013 there were precisely 58,388 ground balls, 1,344 of which resulted in errors. On the other hand a mere 98 out of 39,328 fly balls resulted in errors. That means that 2.3% of ground balls result in errors while a tiny 0.25% of fly balls do. It’s time to stop pretending that this gap doesn’t exist, because it does.

So now that we know this, what does it mean? Well it means this: ground-ball pitchers will have an ERA that suggests they are better than their actual value, while fly-ball pitchers have the opposite effect. Pitchers who allow contact, additionally, are worse off because every time they allow contact they put pressure on their defense. They’re giving themselves a chance to stockpile unearned runs which nobody will count against them if they’re only looking at ERA derivatives. When it comes to winning baseball games, however, earned runs don’t matter. Runs matter.

I am going to call this the “pressure on the defense” effect, which will cause some pitchers to be more prone to unearned runs than other pitchers. How big is this effect? Well, not huge. The gap between the best pitcher and worst pitcher in the league is roughly three runs over the course of the season. But keep in mind that three runs is about a third of a win, and a third of win is worth about $2 million dollars. We’re not discussing mere minutiae here.

In order to better quantify this effect I have developed the xUR/180 metric, which will estimate how many unearned runs should have taken place behind each pitcher with an average defense. Below is a table of all qualified starting pitchers from 2013 ranked according this metric. I have also included how many unearned runs they actually allowed in 2013, scaled to 180 innings for comparative purposes.

#	Name	xUR/180	UR/180
1	Joe Saunders	7.24	9.84
2	Jeff Locke	7.11	4.33
3	Wily Peralta	6.97	17.7
4	Edwin Jackson	6.88	13.36
5	Edinson Volquez	6.81	6.35
6	Kyle Kendrick	6.77	8.9
7	Justin Masterson	6.66	0.93
8	Doug Fister	6.58	5.19
9	Wade Miley	6.57	7.12
10	Rick Porcello	6.51	2.03
11	Jerome Williams	6.47	7.45
12	Jorge de la Rosa	6.43	5.38
13	Yovani Gallardo	6.42	7.99
14	A.J. Burnett	6.35	8.48
15	Scott Feldman	6.32	8.94
16	Mike Leake	6.26	5.62
17	Andrew Cashner	6.25	8.23
18	Felix Doubront	6.22	6.66
19	Jhoulys Chacin	6.13	5.48
20	Kevin Correia	6.13	2.92
21	Jeremy Guthrie	6.13	3.41
22	Mark Buehrle	6.11	5.31
23	Andy Pettitte	6.05	7.78
24	Hyun-Jin Ryu	6.01	2.81
25	Jeff Samardzija	6.0	5.07
26	C.J. Wilson	5.93	11.03
27	CC Sabathia	5.9	8.53
28	Jon Lester	5.84	4.22
29	Ryan Dempster	5.8	10.52
30	Tim Lincecum	5.77	5.48
31	Hiroki Kuroda	5.72	4.48
32	Bud Norris	5.72	7.15
33	Jordan Zimmermann	5.69	3.38
34	Patrick Corbin	5.68	1.73
35	Dillon Gee	5.67	3.62
36	Ervin Santana	5.67	7.68
37	Kris Medlen	5.66	8.22
38	Bronson Arroyo	5.63	2.67
39	Stephen Strasburg	5.62	9.84
40	Mat Latos	5.62	6.85
41	Ubaldo Jimenez	5.61	7.9

#	Name	xUR/180	UR/180
42	Jarrod Parker	5.61	4.57
43	John Lackey	5.6	5.71
44	Gio Gonzalez	5.55	5.53
45	Lance Lynn	5.55	2.68
46	Eric Stults	5.5	7.09
47	Felix Hernandez	5.49	4.41
48	Zack Greinke	5.48	2.03
49	Hisashi Iwakuma	5.47	3.28
50	Jose Quintana	5.46	4.5
51	Ian Kennedy	5.46	8.95
52	Ricky Nolasco	5.45	7.23
53	R.A. Dickey	5.44	6.42
54	Jeremy Hellickson	5.4	3.1
55	Homer Bailey	5.38	3.44
56	Miguel Gonzalez	5.36	9.47
57	Madison Bumgarner	5.34	5.37
58	James Shields	5.32	1.58
59	Adam Wainwright	5.32	2.99
60	Bartolo Colon	5.32	3.79
61	Derek Holland	5.3	7.61
62	Kyle Lohse	5.26	3.63
63	Cole Hamels	5.18	4.91
64	Anibal Sanchez	5.18	3.96
65	David Price	5.18	8.7
66	Chris Sale	5.14	6.73
67	Justin Verlander	5.06	8.25
68	Chris Tillman	5.04	1.75
69	Jose Fernandez	5.03	5.23
70	Shelby Miller	4.98	6.24
71	Matt Cain	4.97	2.93
72	Clayton Kershaw	4.9	5.34
73	Julio Teheran	4.9	2.92
74	Matt Harvey	4.86	1.01
75	Cliff Lee	4.79	4.86
76	Travis Wood	4.78	3.6
77	Dan Haren	4.78	4.26
78	Yu Darvish	4.53	1.72
79	A.J. Griffin	4.46	5.4
80	Mike Minor	4.46	5.29
81	Max Scherzer	4.15	3.36
–	–	–	–

 

Some notes:

• Groundballs are still good, they’re just not as good.
• A combination of groundballs and contact lead to more unearned runs. The pitchers at the top of the board demonstrate this.
• A combination of strikeouts and fly balls will tend to limit the impact of unearned runs, as demonstrated by the bottom of the board.
• Errors that occur on fly balls tend to be more costly than errors on ground balls. This metric accounts for that gap, but the low likelihood of fly-ball errors make this bullet point’s effect relatively negligible.
• Line drives are similar to fly ball in terms of error rate, but they tend to be less costly than fly ball errors.

I’m sure there is more to be gleaned, but the point is this: we need to stop trying to predict ERA, because ERA is not a pure value stat. We should be trying to figure out how many runs a pitcher should/should have given up, because that’s what matters. Runs matter, and who cares if they’re unearned? They’re kind of the pitcher’s fault, anyways.