Verlander and Smyly Among Early Pitching Leaders

Most readers of this blog are aware of the limitations of ERA in evaluating pitcher performance.  Two of the biggest issues are:

(1) ERA gives pitchers full credit/blame for results of batted balls in play despite the fact that they share that responsibility with fielders.  For example, a pitcher with a strong defense behind him will tend to give up fewer hits (and thus fewer runs) than if he had a poor defense behind him.

(2) ERA gives pitchers full responsibility for sequencing or timing of events, that is, it assumes that they can control when they give up hits and walks. For example, if a pitcher pitches extraordinarily well with runners in scoring position in a given year, he will have a lower ERA than if he had a typical year in those situations. Additionally, a pitcher who tends to bunch base runners together in single innings will have a higher ERA than if he had a typical year distributing base runners more evenly.

In reality, pitchers have limited control over both the number of batted balls that drop for hits and sequencing of events.  Thus, Defense Independent Pitching Statistics (DIPS) such as FIP, xFIP, tERA and SIERA have been developed to remove some of the noise of ERA.  DIPS are based on things that pitchers do control for the most part - walks, hit batsmen, strikeouts, home runs and types of batted balls (ground balls , fly balls, line drives, pop flies).

Because they are based on things that pitchers essentially control, the DIPS metrics are said to be better measures of true talent than ERA.  As a result, they are also better than ERA at predicting future performance. However, they only measure a portion of a pitcher's talent and should be used as complements to ERA rather than as replacements.

More and more fans are becoming comfortable with DIPS theory, but it is still a really difficult concept to get across to the mainstream.  If you ever try to explain FIP or any other DIPS statistic to the uninitiated, you will probably find that they are skeptical of a pitching statistic which ignores hits.  They are not likely to buy into it even if they realize the limitations of ERA. 

So, rather than asking fans to take the big leap from ERA to FIP, why not meet them half way?   Instead of removing hit prevention and sequencing in one step, it might be better to remove one factor at a time.  Bill James did that with his Component ERA (ERC).  Applying the runs created methodology to pitchers, he determined what a pitcher's ERA should have been based on walks, hit batsmen,  strikeouts, homers AND hits allowed.  I'm going to look at some similar statistics here based on more modern measures such as linear weights and Base Runs. 

We often use Weighted On-Base Average (wOBA) to measure overall hitting performance and it can also be used for pitchers.  The American League wOBA Against (wOBAA) leaders are shown in Table 1 below.  Tigers ace Justin Verlander is currently third in the league with a .245 wOBAA.  Rookie starter Drew Smyly also ranks among the leaders with a .284 wOBAA. 


Table 1: AL wOBA Against Leaders

Player	Team	IP	wOBAA
Jered Weaver	LAA	50.2	.211
Jake Peavy	CHW	52.1	.225
Justin Verlander	DET	51.1	.245
Jason Hammel	BAL	38.2	.253
Jason Vargas*	SEA	51.2	.259
Gavin Floyd	CHW	46.1	.262
C.J. Wilson*	LAA	41.2	.265
Felix Hernandez	SEA	59.0	.270
Chris Sale*	CHW	33.0	.274
Brandon Morrow	TOR	47.2	.282
CC Sabathia*	NYY	51.1	.283
Drew Smyly*	DET	34.0	.284
Ricky Romero*	TOR	48.0	.285
Jeff Niemann	TBR	33.2	.287
Jake Arrieta	BAL	44.2	.289
Neftali Feliz	TEX	32.0	.294
Tommy Milone*	OAK	43.2	.295
David Price*	TBR	45.1	.295
Jeanmar Gomez	CLE	29.0	.296
Wei-Yin Chen*	BAL	37.0	.297

It's always good to convert to runs allowed when trying to evaluate pitchers, so we'll do that next.  The Base Runs measure was created by David Smythe in the early 1990s.  It is based on the idea that we can estimate team runs scored if we know the number of base runners, total bases, home runs and the typical score rate (the score rate is the percentage of base runners that score on average.  Base Runs also works well for individual pitchers.  The complete formula can be found here.

Justin Verlander has 13 Base Runs Against in 51 1/3 innings so far this year.  This means that he should have allowed an estimated 13 runs based on the number of base runners, total bases and home runs he has allowed.  He has allowed 17 actual runs, so runs are scoring against him at a higher rate than you would expect so far.  That could possibly be due to bad defense, unfortunate timing or just bad luck on locations of batted balls.

Verlander has 11 Base Runs Above Average (RAA) which means that he has saved the Tigers an estimated 11 runs compared to the average pitcher in the same number of innings.  Table 2 shows that he is tied for third in the American League on that metric.  Smyly is 14th with 4 RAA. 

Table 2: AL Runs Above Average Leaders

Player	Team	IP	Base Runs	RAA
Jered Weaver	LAA	50.2	9	14
Jake Peavy	CHW	52.1	11	14
Justin Verlander	DET	51.1	13	11
Felix Hernandez	SEA	59.0	17	11
Gavin Floyd	CHW	46.1	13	9
Jason Vargas*	SEA	51.2	16	9
Jason Hammel	BAL	38.2	10	8
C.J. Wilson*	LAA	41.2	13	7
Ricky Romero*	TOR	48.0	17	5
CC Sabathia*	NYY	51.1	19	5
Chris Sale*	CHW	33.0	11	5
Brandon Morrow	TOR	47.2	18	5
David Price*	TBR	45.1	17	5
Drew Smyly*	DET	34.0	12	4
Tommy Milone*	OAK	43.2	16	4
Jeff Niemann	TBR	33.2	12	4
Neftali Feliz	TEX	32.0	12	4
Henderson Alvarez	TOR	48.1	19	3
Derek Holland*	TEX	46.2	19	3
Jake Arrieta	BAL	44.2	18	3

Finally, Table 3 shows that Verlander has allowed 2.26 Base Runs per nine innings.  About 93% of runs are earned, so multiply this result by .93. to put it on the same scale as ERA. The final result is a weighted component ERA.  Although, I am not using linear weights here, I call it WERC because others have said the like the name. It's really not a novel idea though.  Toirtap of Walk Like a Saber has been using Base Runs to evaluate pitchers for a while but prefers to not convert to the ERA scale.

Getting back to the example, Verlander has a 2.26 WERC which again is third in the league.  This is worse than his actual ERA of 2.63 which indicates that he may be pitching better than his ERA suggests.  Smyly's WERC of 2.93 is not as good as his league-leading 1.59 ERA, but is probably more reflective of how he has pitched - very well, but not the best pitcher in the league.   


Table 3: AL WERC Leaders

Player	Team	IP	Base Runs/9 IP	WERC
Jered Weaver	LAA	50.2	1.69	1.57
Jake Peavy	CHW	52.1	1.90	1.76
Justin Verlander	DET	51.1	2.26	2.10
Jason Hammel	BAL	38.2	2.45	2.28
Gavin Floyd	CHW	46.1	2.57	2.39
Felix Hernandez	SEA	59.0	2.63	2.45
Jason Vargas*	SEA	51.2	2.77	2.57
C.J. Wilson*	LAA	41.2	2.81	2.62
Chris Sale*	CHW	33.0	2.94	2.73
Drew Smyly*	DET	34.0	3.15	2.93
Ricky Romero*	TOR	48.0	3.23	3.00
Neftali Feliz	TEX	32.0	3.27	3.04
Jeff Niemann	TBR	33.2	3.27	3.05
David Price*	TBR	45.1	3.32	3.09
Brandon Morrow	TOR	47.2	3.34	3.10
Jeanmar Gomez	CLE	29.0	3.37	3.13
CC Sabathia*	NYY	51.1	3.40	3.16
Tommy Milone*	OAK	43.2	3.41	3.17
Jake Arrieta	BAL	44.2	3.61	3.35
Derek Holland*	TEX	46.2	3.61	3.36

Note: The raw data used in the above calculations were taken from Baseball-Reference.com