Poll: Which Group of Pitchers Performs Better?

If you are familiar with my feelings on pitchers, you know that I put little stock in ERA over smaller samples. Instead, I choose to largely ignore perhaps the most accepted metric to describe a pitcher’s performance by focusing on his peripherals and ERA estimators, my favorite of which is SIERA. Sure, over a long career, ERA is most certainly the better of the two to judge a player’s performance, but at the all-star break of a season, give me SIERA. With most starting pitchers having thrown only about 120 innings, the sample size remains far too small for ERA to provide significant predictive value over the remainder of the season.

Of course, it’s hard to ignore ERA. Do you think a Matt Cain owner wants to hear that his pitcher has simply suffered from some poor fortune? Of course not. It’s human nature to place a greater emphasis on the most recent past (recency bias) and since ultimately it’s the earned runs that count, not the imaginary expected runs SIERA believes a pitcher should have allowed, then ERA is the statistic that is focused on.

So as we sit here and wonder how Jeff Locke and Travis Wood parlayed fantastic defensive support into an All-Star appearance, I decided that it would be fun to play a little game. Below are two groups of pitchers. Group A is composed of the 10 pitchers whose ERA sits most below their SIERA marks. Group B, on the other hand, features the 10 pitchers whose ERA exceed their SIERA marks by the largest amount. The game is simple: vote for which group of pitchers posts a better ERA after the All-Star break through the remainder of the season. Don’t forget to also vote for which range each group’s ERA will fall into through the rest of the season.

I will be closing the polls right before the first pitch when games resume on Friday. At the end of the season, I will revisit this post and publish the results of the voting, as well as the performances of the pitcher groups. For the record, I vote for group B.

Group A – The SIERA Outperformers

Name	IP	K%	BB%	BABIP	LOB%	HR/FB	ERA	SIERA	Diff
Jeff Locke	109.0	16.7%	10.8%	0.228	83.3%	6.7%	2.15	4.56	-2.41
Travis Wood	122.2	17.6%	7.8%	0.227	76.5%	5.8%	2.79	4.45	-1.66
Bartolo Colon	126.2	14.0%	3.0%	0.287	80.2%	6.0%	2.70	4.19	-1.49
Mike Leake	117.0	15.0%	5.5%	0.260	79.6%	10.0%	2.69	4.11	-1.42
Jason Marquis	112.1	14.7%	13.2%	0.256	79.7%	19.6%	3.77	5.11	-1.34
Clayton Kershaw	145.1	24.8%	6.3%	0.238	78.7%	5.4%	1.98	3.24	-1.26
Patrick Corbin	130.1	21.2%	6.4%	0.246	81.9%	7.8%	2.35	3.61	-1.26
Hiroki Kuroda	118.2	17.7%	5.1%	0.252	82.6%	9.8%	2.65	3.88	-1.23
Jorge de la Rosa	109.1	16.6%	8.5%	0.294	76.4%	6.7%	3.21	4.32	-1.11
Bronson Arroyo	123.2	13.7%	4.6%	0.254	78.9%	11.6%	3.42	4.41	-0.99
Average	121.2	17.4%	7.0%	0.253	79.6%	8.8%	2.74	4.15	-1.40

Group B – The SIERA Underperformers

Name	IP	K%	BB%	BABIP	LOB%	HR/FB	ERA	SIERA	Diff
Joe Blanton	112.1	18.2%	5.1%	0.343	70.6%	18.1%	5.53	3.85	1.68
Wade Davis	94.2	19.9%	9.4%	0.381	66.3%	13.5%	5.89	4.21	1.68
Rick Porcello	99.1	19.4%	4.6%	0.317	65.4%	15.7%	4.80	3.15	1.65
Edinson Volquez	109.2	18.8%	10.2%	0.342	63.3%	8.8%	5.74	4.31	1.43
Edwin Jackson	100.1	19.5%	8.1%	0.320	62.3%	10.6%	5.11	3.83	1.28
Roberto Hernandez	108.1	18.2%	5.4%	0.304	69.7%	21.2%	4.90	3.63	1.27
Matt Cain	112.0	22.1%	7.9%	0.257	63.4%	12.7%	5.06	3.84	1.22
Ian Kennedy	108.0	19.1%	8.4%	0.298	67.1%	12.6%	5.42	4.26	1.16
Jeremy Hellickson	117.2	20.3%	5.5%	0.296	66.9%	10.8%	4.67	3.74	0.93
Yovani Gallardo	113.2	18.3%	8.7%	0.310	65.7%	12.5%	4.83	4.10	0.73
Average	107.2	19.3%	7.3%	0.315	65.9%	13.6%	5.17	3.88	1.29