There is no surefire way to determine the best pitcher in the league, but a pitchers job is to prevent runs. So, it's useful to estimate how many runs pitchers saved their teams compared to an average pitcher. As the regular season wound down, I 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.
If we attempt to take team defense out of the equation, then Scherzer looks better since Detroit had one of the three worst defenses according to Defensive Runs Saved and Total Zone in the AL along with the Mariners and White Sox. According to Adjusted Pitching Runs which considers defense as well as ballpark, Scherzer finished with 37 Adjusted Pitching Runs which was second to Sanchez (38). The biggest limitations of this metric arer 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 baserunners and extra base hits, he might get away with a relatively low ERA one year 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 baserunners 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 used 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 had a comfortable lead with 37 Base Runs which was 10 runs better than Darvish (27) the runner up.
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 31 FIP Runs which was second to Sanchez at 33.
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 was 33 which was the best in the league. He was followed by Sanchez (31) and Darvish (29).
So, based on this aggregate measure, Scherzer appears to be the deserving winner of the award he will likely soon reap.
Table 1: American League Runs Above Average Leaders, 2013
Team | IP | Pitching Runs | Adjusted Pitching Runs | Base Runs | FIP Runs | Average | |
Max Scherzer | DET | 214.1 | 29 | 37 | 37 | 31 | 33 |
Anibal Sanchez | DET | 182.0 | 31 | 38 | 24 | 33 | 31 |
Yu Darvish | TEX | 209.2 | 32 | 36 | 27 | 22 | 29 |
Hisashi Iwakuma | SEA | 219.2 | 36 | 37 | 26 | 7 | 26 |
Chris Sale* | CHW | 214.1 | 21 | 33 | 26 | 23 | 26 |
Felix Hernandez | SEA | 204.1 | 23 | 24 | 23 | 27 | 24 |
Bartolo Colon | OAK | 190.1 | 31 | 32 | 18 | 14 | 24 |
Justin Masterson | CLE | 193.0 | 17 | 18 | 26 | 11 | 18 |
James Shields | KCR | 228.2 | 27 | 14 | 16 | 8 | 16 |
Hiroki Kuroda | NYY | 201.1 | 17 | 21 | 13 | 12 | 16 |
Justin Verlander | DET | 218.1 | 10 | 19 | 8 | 19 | 14 |
David Price* | TBR | 186.2 | 11 | 7 | 19 | 17 | 13 |
Doug Fister | DET | 208.2 | 8 | 17 | 9 | 18 | 13 |
Jose Quintana* | CHW | 200.0 | 12 | 24 | 8 | 8 | 13 |
Derek Holland* | TEX | 213.0 | 12 | 14 | 6 | 18 | 12 |
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