Scherzer Leads AL in Run Prevention

Tigers right hander Max Scherzer's season looks great by any pitching metric.
(Photo credit: Yahoo Sports)

It's time for the first installment of the Tiger Tales sabermetric pitching Leaders in 2014.  

There is no surefire way to determine the best pitchers in the league, but a pitcher's job is to prevent runs.  So, it's useful to estimate how many runs pitchers saved their teams compared to an average pitcher.  In the past, I have explored four different ways to do this:    

• Pitching Runs -  Runs Saved Above Average based on innings and runs allowed. 

• Adjusted Pitching Runs - Pitching Runs minus estimated Runs allowed by fielders. 

• Base Runs -  Runs Saved Above Average based on batters faced and hits, walks, total bases and home runs allowed.

• FIP Runs - Runs Saved Above Average based on innings, bases on balls, hit batsmen and home runs allowed and strikeouts.

Tigers starter Max Scherzer leads the American League with 14 Pitching Runs so far this year which indicates that he saved the Tigers an estimated 14 runs compared to the average pitcher in the same number of innings.  A statistic based on pure runs allowed is a good place to start, but it does not take into consideration things such as team defense and ballparks.

If we attempt to take team fielding out of the equation, then Scherzer looks better since the Tigers have performed below average defensively so far according the Total Zone and Defensive Runs Saved Statistics. According to Adjusted Pitching Runs which considers defense as well as ballpark, Scherzer has saved his team a league-leading 16 runs.  The biggest limitations of this metric are the uncertainty of the fielding measures and the assumption that all pitchers are affected by team defense in the same way.  

Even if you trust the fielding component of the Adjusting Pitching Runs calculation, another issue is that a pitcher has no control over what happens after he leaves the game   If he departs with a man on first with two outs and the relief pitcher allows a run-scoring double, the starting pitcher is charged with the run. In other words, a pitcher’s ERA is dependent not only on the quality of his innings but also on the quality of the innings of his relievers.

Another potential concern regarding Pitching Runs and Adjusted Pitching Runs is the timing of hits, walks and extra base hits. For example, if a pitcher pitches nine innings and gives up nine hits with each hit coming in a different inning, he will almost surely allow fewer runs than if he surrenders all the hits in one
inning. If a pitcher frequently allows a lot of base runners and extra base hits, he might get away with a relatively low ERA for a period of time, but it wouldn't necessarily be based on skill.

A related issue to the distribution of base runners is sequencing of events. Let’s say a pitcher
allows the following sequence of events in an inning:

1. Ground out
2. Single
3. Single
4. Homer
5. Strikeout
6. Fly out

In this case, he would be charged with three runs allowed for the inning. Now, suppose that
Pitcher B has a slightly different sequence of events in another inning:

1. Ground out
2. Homer
3. Single
4. Single
5. Strikeout
6. Fly out

In this case, the pitcher is charged with one run. Both pitchers surrendered a homer and two
singles but Pitcher B allowed two fewer runs just because the sequence of hits was different.

While pitchers vary in their ability to prevent base runners from scoring, research by Ron Shandler – author of The Baseball Forecaster and publisher of BaseballHQ.com– suggests that this has more to do with overall pitcher quality than clutch pitching ability. In other words, most pitchers who consistently strand runners do so primarily because they get strikeouts and limit base runners in all situations, not because they have a lot of control over clustering of base runners or sequencing of events.  In other words, much of the bunching and sequencing seems to based on luck to some extent.  

In order to remove, clustering of base runners and sequencing of events from the equation, we can use a component-based statistic.  One such measure is the Base Runs statistic 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 9 Base Runs which ties him for the league lead with Athletics starter Scott Kazmir, Garrett Richards of the Angels and Felix Hernandez of Seattle.   

A criticism of Base Runs for evaluation of pitchers is that it includes hits on balls in play which is the responsibility of fielders at least as much as pitchers.  Thus, many analysts prefer to use FIP (translated in to FIP Runs here) which only considers events that a pitcher essentially controls - walks, hit batsmen and home runs allowed and strikeouts.  Scherzer had 11 FIP Runs which was second to Red Sox right hander Jon Lester (13).  

Table 1 below lists all four statistics discussed above - Pitching Runs, Adjusted Pitching Runs, Base Runs and FIP Runs - side by side and also the average of the four for the top fifteen pitchers.  Scherzer's average across the measures is 13 which leads the American League.  He is followed by three Oakland starters - Sonny Gray (10), Kazmir (8) and Jesse Chavez (8).  

Scherzer's teammate Justin Verlander is 10th with 6 Runs Saved.  Other Tigers starters include Rick Porcello (4), Drew Smyly (4) and Anibal Sanchez (3).

Table 1: AL Run Prevention Leaders as of May 5, 2014

Pitcher	Team	IP	Pitching Runs	Adjusted Pitching Runs	Base Runs	FIP Runs	Average
Max Scherzer	DET	47.0	14	16	9	11	13
Sonny Gray	OAK	47.0	11	11	8	7	10
Scott Kazmir*	OAK	44.1	8	8	9	8	8
Jesse Chavez	OAK	38.0	8	8	8	8	8
Yordano Ventura	KCR	36.0	9	8	7	7	8
Garrett Richards	LAA	38.0	7	6	9	7	7
Jon Lester*	BOS	48.2	3	6	7	13	7
Masahiro Tanaka	NYY	42.2	8	10	4	6	7
Mark Buehrle*	TOR	40.0	8	9	3	6	7
Justin Verlander	DET	47.0	5	8	4	8	6
Felix Hernandez	SEA	46.1	4	3	9	9	6
Yu Darvish	TEX	37.2	7	8	3	7	6
Martin Perez*	TEX	47.2	4	7	6	7	6
Zach McAllister	CLE	39.2	4	6	4	8	5
Kyle Gibson	MIN	36.0	4	5	5	3	4
C.J. Wilson*	LAA	39.2	5	3	5	5	4
John Lackey	BOS	46.0	3	5	2	6	4
Rick Porcello	DET	32.0	3	4	4	4	4
Corey Kluber	CLE	45.0	1	4	2	8	4

Data source: Baseball-Reference.com