Scherzer's Stuff is WERCing This Year

Today, I'll continue my series on lesser known metrics for evaluating pitchers.  In my previous post, I looked at simple run prevention just based on runs allowed and innings pitched.  Most readers of this blog are aware of the limitations of just looking at ERA or Run Average (RA) in evaluating pitcher performance.  Two of the biggest issues are:

• RA 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 has a poor defense behind him.

• RA 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 RA.  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 RA.  As a result, they are also better than RA at predicting future performance. However, they only measure a portion of a pitcher's talent and should be used as complements to RA rather than as replacements. 

It is not known exactly how much control pitchers have on the results of balls in play, but recent research tells us that some pitchers are better than others at preventing hits on balls in play.  For example, Mike Fast, formerly of Baseball Prospectus and now a MLB sabermetrician, used Sportsvision's hit f/x data to show how pitchers varied on the speed of balls off the bat.

So, rather than making the big leap from RA to FIP, it might be a good idea to first meet 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 Max Scherzer currently leads the league by a wide margin with a .253 wOBAA.  Teammate Anibal Sanchez is second at .270, with Rangers right hander Yu Darvish third at .272. 
 

Table 1: AL wOBA Against Leaders

Player	Team	G	IP	wOBAA
Max Scherzer	DET	28	190.1	.253
Anibal Sanchez	DET	24	151.1	.270
Yu Darvish	TEX	27	179.2	.272
Chris Sale*	CHW	26	187.2	.275
Hisashi Iwakuma	SEA	29	191.0	.278
Felix Hernandez	SEA	29	194.1	.281
Justin Masterson	CLE	29	189.1	.285
David Price*	TBR	21	144.1	.288
Hiroki Kuroda	NYY	28	177.2	.289
Jarrod Parker	OAK	28	176.1	.292
Bartolo Colon	OAK	26	164.1	.294
Jered Weaver	LAA	21	135.1	.295
Ervin Santana	KCR	28	184.0	.295
James Shields	KCR	29	196.0	.297
Jose Quintana*	CHW	28	165.2	.300
Derek Holland*	TEX	28	184.2	.301
C.J. Wilson*	LAA	28	177.1	.304
A.J. Griffin	OAK	28	176.0	.304
John Lackey	BOS	25	162.1	.306
Justin Verlander	DET	29	185.2	.308

 Data source: Baseball-Reference

It's generally a good thing to convert to runs allowed when trying to evaluate pitchers, so I'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.

Scherzer has 57 Base Runs Against in 190 1/3 innings so far this year.  This means that he should have allowed an estimated 57 runs based on the number of base runners, total bases and home runs he has allowed.  He has allowed 64 actual runs, so runs are scoring against him at a higher rate than you would expect so far.

The discrepancy between Base Runs and Runs Allowed is probably due to sequencing of events mentioned above and also in the comments section of the previous post.  It could have something to do with bunching of base runners or pitching with runners in scoring position.  Should this kind of situational pitching be included in a Cy Young discussion?  It's a popular topic with no consensus answer in the sabermetric community.  I am deliberately excluding it from the metrics in this particular post, but I think it's something worth looking at. 

Scherzer has 36 Base Runs Above Average (RAA) which means that he has saved the Tigers an estimated 36 runs compared to the average pitcher in the same number of innings.  Table 2 shows that he also leads the league by a healthy margin on that metric.  White Sox southpaw Chris Sale and Justin Masterson of the Indians are tied for second with 26.      

Table 2: AL Runs Saved Leaders

Player	Team	G	IP	Base Runs	RAA
Max Scherzer	DET	28	190.1	57	36
Chris Sale*	CHW	26	187.2	65	26
Justin Masterson	CLE	29	189.1	66	26
Yu Darvish	TEX	27	179.2	63	24
Felix Hernandez	SEA	29	194.1	71	24
Anibal Sanchez	DET	24	151.1	52	22
Hisashi Iwakuma	SEA	29	191.0	71	22
Hiroki Kuroda	NYY	28	177.2	69	17
James Shields	KCR	29	196.0	79	17
Jarrod Parker	OAK	28	176.1	70	16
David Price*	TBR	21	144.1	55	15
Bartolo Colon	OAK	26	164.1	65	14
Ervin Santana	KCR	28	184.0	76	14
Doug Fister	DET	28	179.2	75	12
Jered Weaver	LAA	21	135.1	55	11
Derek Holland*	TEX	28	184.2	79	11
Jose Quintana*	CHW	28	165.2	72	9
John Lackey	BOS	25	162.1	71	8
C.J. Wilson*	LAA	28	177.1	79	7
Justin Verlander	DET	29	185.2	85	5

Data source: Baseball-Reference 
 
Finally, Table 3 shows that Scherzer has allowed 2.68 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 they like the name. It's really not a novel idea though.  Patriot 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. The only reason I convert to the ERA scale is to allow for simple comparison with ERA and FIP. 

Getting back to the example, Scherzer has a 2.49 WERC which again makes him the clear league leader.  This is a little lower than his ERA (2.88) and FIP (2.72), which again suggests a small bit of unfortunate sequencing.  

Table 3: AL WERC Leaders 

Player	Team	G	IP	Base Runs/9 IP	WERC
Max Scherzer	DET	28	190.1	2.68	2.49
Anibal Sanchez	DET	24	151.1	3.07	2.86
Chris Sale*	CHW	26	187.2	3.11	2.89
Justin Masterson	CLE	29	189.1	3.13	2.91
Yu Darvish	TEX	27	179.2	3.18	2.96
Felix Hernandez	SEA	29	194.1	3.28	3.05
Hisashi Iwakuma	SEA	29	191.0	3.36	3.13
David Price*	TBR	21	144.1	3.44	3.20
Hiroki Kuroda	NYY	28	177.2	3.52	3.27
Jarrod Parker	OAK	28	176.1	3.55	3.30
Bartolo Colon	OAK	26	164.1	3.59	3.34
James Shields	KCR	29	196.0	3.61	3.36
Jered Weaver	LAA	21	135.1	3.63	3.38
Ervin Santana	KCR	28	184.0	3.69	3.44
Doug Fister	DET	28	179.2	3.78	3.52
Derek Holland*	TEX	28	184.2	3.85	3.58
Jose Quintana*	CHW	28	165.2	3.90	3.63
John Lackey	BOS	25	162.1	3.96	3.68
C.J. Wilson*	LAA	28	177.1	4.04	3.75
Justin Verlander	DET	29	185.2	4.12	3.83

Data source: Baseball-Reference   

So, if  you give Scherzer credit for all of run prevention except sequencing, then his Cy Young candidacy looks very strong. Of course, there is still the sticky problem of what do with hits which are included here.  You could attribute hits to how hard balls are hit, fielding or bad luck, but we don't know to what extent any of those things are happening for a particular pitcher.  Therefore, it's useful to see where they stand if hits are taken into account along with looking at DIPS metrics.