# Getting Friendly with Pitcher K%

This sunset has a pretty high Glory Factor (GF).

The attentive reader will note that FanGraphs Dark Overlord David Appelman has recently descended from atop his inlaid throne and made some changes to the way that strikeouts are presented in these pages. For batters now, strikeout percentage (K%) uses plate appearances, and not at-bats, in the denominator. While this creates pretty substantial (ca. 6%) movement for Three True Outcome-ist Adam Dunn, most players exhibit a fairly uniform decrease of about 2%, meaning that readers are able to mentally convert to the new format with some ease.

The addition of strikeout percentage (also K%) for *pitchers*, however — while glorious as the sunset over Quetena Chico — makes for a slightly more challenging mental covnersion, as readers will undoubtedly have become quite accustomed to assessing pitchers using strikeouts per nine innings (K/9).

As Mr. Matt Swartz demonstrated in these pages yesterday, however, knowing a pitcher’s K% is important for at least two reasons (in that it’s predictive of BABIP allowed and home runs per fly ball). Beyond that, K% is plainly the more accurate representation of what we’re intending when we cite K/9 — namely, to note which pitcher or pitchers are the best at inducing strikeouts.

To aid the readership in its transition from K/9 to K%, below are some notes on the two metrics and their relaionship with each other, including some illustrations of K/9’s weaknesses.

**1. K/9 and K%: A Stong Correlation**

It probably won’t come as a shock to learn that K/9 and K% correlate strongly. Here, for example, is a graph looking at the relationship between K/9 and K% for all 257 qualified starting pitchers between 2008 and’10.

As you can see, the correlation is something in the vicinity of 0.99. While there are certainly some outliers, the conversion between K% and K/9 is a pretty regular one.

**2. Converting Between K% and K/9**

Because the correlation between K/9 and K% is so stong, the following quick conversion table (using the formula from the above graph) will serve you well in almost every case (K/9 is *expected* K/9 given K%):

**3. Some Benchmarks for K%**

While readers will no doubt have an intuitive sense of what constitutes a good (and not-so-good) K/9, it’s likely that K% is a trickier subject. For your edification, then, below is a summary of K% in context (*à la mode* of House Librarian Steve Slowinski), using number from 2011’s 106 qualified pitchers.

**4. A Look at Some Outliers**

Though predictive in *most* cases, the formula to convert K% to “expected” K/9 (or, xK/9 below) produces some outliers. These outliers are actually *helpful*, as they call attention to those aspects of strikeout-inducing that K/9 misses, but which K% identifies accurately.

Firstly, here are the 10 qualified pitchers from 2008 to ’10 whose K/9 most *underrated* strikeout ability:

And now, here are the 10 qualifiers whose K/9 most *overrated* strikeout ability:

**5. A Look at Some Outliers, Part II**

Looking at the two charts above, you probably already get some sense of the differences between the pitchers who’re under- and overrated by K/9. For example, Roy Halladay and Cliff Lee and Zack Greinke are really good. Ian Snell, on the other hand, is more of a “minor leaguer.”

In any case, to make the relationship clear, here are the averages for each set of 10 pitchers in some notable categories:

**Underrated Pitchers**

BB/9: 1.77

BB%: 4.98%

BABIP: .274

xFIP-: 79

**Overrated Pitchers**

BB/9: 3.65

BB%: 9.11%

BABIP: .323

xFIP-: 96

As you can see, the overrated group was actually *rewarded* with higher K/9s because they extended innings through walks and hits on batted balls. While the latter category is likely part bad luck, the former is certainly not. The advantage of K% is that it represents precisely how many batters are being struck out and rewards efficiency.

*Image courtesy Jeronimo’s Eye.*

Print This Post