A Letter to a Young, Inconsistent Pitcher
Imagine, for a moment, that you’re a young pitcher who has been slapped (fairly or unfairly) with a reputation for inconsistency by the local media. You realize all the possible ill effects, from salary implications to fan relations, such a label could have on your career. What could we possibly tell you to do? In short, my advice is to finish the year better than you started.
We’ve been discussing consistency recently here on BP, particularly with regard to starting pitchers. In the immediate context of the season, nothing is more frustrating than inconsistency, whether from a team or a player. Consistency is one of those fleeting notions seen only at the periphery of statistics; the more you focus on it, the more ephemeral it becomes. And while you’ll certainly find those who swear up and down that it is valuable, you’ll find nearly as many who claim consistency with value in and of itself is as ridiculous a notion as turkey bacon.
While I’m as much a sucker for numbers as the next guy, every once in a while I like to look at my data in a more immediate way. So I’ve followed a pretty simple method: I’ve taken the first two current major-league pitchers to appear twice in a Google News search for the terms “consistent baseball” as well as the first two pitchers to appear twice in a similar search for the terms “inconsistent baseball.” What my method lacks in sophistication, it compensates for with simplicity and accessibility. One nice thing about this way of going about it is that the choices were made for me; all that remains is testing them.
First, let’s introduce our contestants. The consistent: CC Sabathia and Joe Blanton. The inconsistent: Chad Billingsley and Joel Pineiro. It’s worth noting that none of these pitchers are particularly bad, but summed together the “consistent” pitchers are the better pair. Here are their simple, combined 2009 statistics.
The two pairs match up relatively well, but the “consistent” pitchers strike out and walk more batters. As a result, they allowed fewer runs per inning last year. But the question remains how well each label fits.
The LOWESS Branch on the FIGS Tree
For the purposes of this exercise, I’ve adopted the form of fielding-independent game score (FIGS) favored by Fungoes. Their implementation of the stat is as follows: 50+BF/3+2*SO-2*BB-8*HR. I have taken all the starts for our four pitchers and calculated a FIGS value for each. I’ve then plotted the starts in chronological order, with FIGS on the y-axis. I’ve then applied a local regression line to filter out some of the noise visually. (It’s a LOWESS regression with a smoothing factor of
Let’s take a look at the consistent group, starting with CC “splish splash, I was taking” Sabathia:
Sabathia appears, visually, to be rather consistent. The regression line is rather flat, and the range of the FIGS is approximately 30. He was markedly better after his 20th (or so) start. Now let’s look at his consistent team partner, Joe Blanton (perceived to be the innings eater’s innings eater):
Blanton, too, appears relatively consistent from the regression line. However, his individual starts were distributed somewhat more widely, and the range on his FIGS was closer to 45 than Sabathia’s 30. Like Sabathia, Blanton was better in the second half of the season than he was in the first. Blanton, however, tailed off a little at the end of the year.
How about the inconsistent group? Here’s Billingsley, whose inconsistency bumped him from the Dodgers‘ playoff rotation:
Billingsley, as you can see, declined “consistently” over the course of the season. Although he started strong, he did not finish well at all. His starts also varied in quality as the season progressed. His range of approximately 40, however, was superior to Blanton’s. How about Pineiro, who put together a renaissance season under the tutelage of Dave Duncan in St. Louis?
Pineiro also tailed off a little at the end of the season, but ever so imperceptibly. From May through September, he was more or less the same pitcher. Additionally, over the same period, his starts cluster very close to his average performance, suggesting Pineiro was indeed rather consistent. One bad start in September rendered Pineiro’s range at about 35. Absent the outlier, his range would have been approximately 20.
In the end, I’m not sure how much we can learn from the lessons of just four pitchers. A few caveats bear noting. First, a reputation for consistency (or lack thereof) is presumably something that develops over many seasons, and so looking at just last year’s data may not tell the full story. Additionally, by using FIGS, I am obscuring the impact that balls in play have on perceived consistency in the form of runs scored. However, viewing the FIGS data visually does bring into relief some interesting phenomena. The consistent pitchers finished stronger than the inconsistent ones relative to their seasonal baselines. Interestingly, the consistent pitchers did not cluster their performances any more closely than the inconsistent ones did. It also bears noting that Pineiro, who in fact may have been the most consistent of the four despite his “inconsistent” label, enjoyed a sharp spike in ground-ball rate last season (by any batted ball classification data). Whether ground-ball pitchers are more consistent on a metric like FIGS, or whether there was some third factor that caused Pineiro’s ground ball rate to spike with his consistency (call it the Duncan Effect), remains unclear.
Question of the Day
What advice would you give to a young pitcher seeking to gain a reputation for consistency? Are there factors (other than pitching well all the time) that might help a pitcher gain such a reputation? Is this the sort of thing that a pitcher can have control over?