CAIN: Counting a Pitcher’s HR/FB Out-Performance
Dave Cameron recently posted an interesting article about Jhoulys Chacin. It’s all about how Jhoulys Chacin is defying the rules of HR/FB rates. His HR/FB rate this year is a mere 2.8%. Jhoulys Chacin has pitched 120 innings, had 106 fly balls, and allowed just three home runs. Very impressive. But it makes you wonder if there are other pitchers who are maintaining low rates while allowing more fly balls overall. Because while Jhoulys Chacin is obviously benefiting from his HR/FB ratio, it’s possible for a pitcher to have more fly balls while maintaining a slightly higher HR/FB and benefit more. So I invented CAIN, a counting stat to help measure that.
CAIN does not stand for anything. I’m just paying homage to a famous outlier.
CAIN = FB – (9.34 x HR)
To explain, the Fangraphs Glossary says that the league-average fly ball rate is “~9-10% depending on the year”. In fact, of the 91 qualified pitchers in Fangraphs database for 2013, the average HR/FB ratio is 10.7 percent. So there are 9.34 fly balls for every homer. So we can say that for most pitchers, if they had ten homers at this point in the season, they would have about 93.4 fly balls. Ten homers and 93.4 fly balls would give you a CAIN of exactly 0. Make sense?
Now for what you came here for. Here are the top ten in CAIN this year:
Note that I’m not saying any players might actually be able to sustain their CAIN, I just think it’s an interesting little tidbit, and perhaps a nice follow on to Dave Cameron’s article.
Name | Team | IP | HR | FB | CAIN | HR/FB |
---|---|---|---|---|---|---|
Eric Stults | Padres | 133 | 8 | 163 | 88.3 | 4.90% |
Jhoulys Chacin | Rockies | 120 | 3 | 106 | 78 | 2.80% |
Bartolo Colon | Athletics | 135.2 | 9 | 161 | 76.9 | 5.60% |
Travis Wood | Cubs | 128.1 | 10 | 159 | 65.6 | 6.30% |
Adam Wainwright | Cardinals | 154.2 | 6 | 113 | 57 | 5.30% |
Bud Norris | Astros | 119.2 | 10 | 150 | 56.6 | 6.70% |
Lance Lynn | Cardinals | 122 | 7 | 121 | 55.6 | 5.80% |
Matt Moore | Rays | 116.1 | 8 | 130 | 55.3 | 6.20% |
Derek Holland | Rangers | 133.2 | 9 | 137 | 52.9 | 6.60% |
Clayton Kershaw | Dodgers | 152.1 | 9 | 136 | 51.9 | 6.60% |
And Jhoulys Chacin is not #1. It turns out that Eric Stults is in fact benefiting more from his HR/FB rate outlier this year. Of course, that’s partially happening in Petco. Petco is not Coors.
Name | Team | IP | HR | FB | CAIN | HR/FB |
---|---|---|---|---|---|---|
Joe Blanton | Angels | 116 | 24 | 133 | -91.2 | 18.0% |
Roberto Hernandez | Rays | 113.1 | 18 | 91 | -77.1 | 19.8% |
Jason Marquis | Padres | 117.2 | 18 | 99 | -69.1 | 18.2% |
CC Sabathia | Yankees | 142 | 23 | 150 | -64.8 | 15.3% |
Chris Tillman | Orioles | 119.2 | 21 | 135 | -61.1 | 15.6% |
Ryan Dempster | Red Sox | 115.2 | 20 | 130 | -56.8 | 15.4% |
R.A. Dickey | Blue Jays | 134.2 | 23 | 163 | -51.8 | 14.1% |
Jeremy Guthrie | Royals | 126.2 | 22 | 155 | -50.5 | 14.2% |
Hisashi Iwakuma | Mariners | 138.1 | 21 | 146 | -50.1 | 14.4% |
Lucas Harrell | Astros | 112 | 15 | 96 | -44.1 | 15.6% |
Poor Joe Blanton. His peripherals aren’t that bad this year. But he’s been posting some pretty high HR/FB rates for the last five years or so. I’ll leave it to someone else to puzzle that out.
After doing this analysis I wanted to know about exceptional seasons in the “UZR era” for pitchers’ CAINs. I am continuing to use 9.34 as the FB/HR value, not adjusted for year. If I was being very scientific I would probably break that constant out for league AND year, but I’m lazy and unpaid. Anyway, here, unsurprisingly, is Matt Cain:
Season | Name | Team | IP | HR | FB | HR/FB | CAIN |
---|---|---|---|---|---|---|---|
2011 | Matt Cain | Giants | 221.2 | 9 | 246 | 3.70% | 161.94 |
2007 | Chris Young | Padres | 173 | 10 | 243 | 4.10% | 149.6 |
2002 | Jarrod Washburn | Angels | 206 | 19 | 317 | 6.00% | 139.54 |
2009 | Zack Greinke | Royals | 229.1 | 11 | 242 | 4.50% | 139.26 |
2002 | Mark Redman | Tigers | 203 | 15 | 273 | 5.50% | 132.9 |
2011 | Jered Weaver | Angels | 235.2 | 20 | 319 | 6.30% | 132.2 |
2010 | Anibal Sanchez | Marlins | 195 | 10 | 222 | 4.50% | 128.6 |
2010 | Livan Hernandez | Nationals | 211.2 | 16 | 278 | 5.80% | 128.56 |
2010 | Jason Vargas | Mariners | 192.2 | 18 | 295 | 6.10% | 126.88 |
2007 | Matt Cain | Giants | 200 | 14 | 255 | 5.50% | 124.24 |
So in summary, CAIN is a nice little tool if you are interested in seeing just how much a HR/FB rate is affecting a pitcher’s performance. If anyone can think of a better acronym, like one that actually is an acronym, please leave a comment.
White Sox fan.
Thank you for putting this up. It was fun to write. Three comments. First, I don’t know how to post a sortable table. Is there a section of this site that explains this?
Second, I have no idea if there is already a similar stat out there.
Third, I refer to this as a “counting” stat. And it is: it counts the number of flyballs that occurred in excess of the expected flyballs given the player’s home runs. I don’t think I made that clear above.
However, it occurs to me that this might be counterintuitive. I think in the future I could change the stat to be HR – FB/9.3. That would be in other words the difference of home runs versus expectations based on their flyball rate. Although those numbers wouldn’t be as big and therefore wouldn’t be as much fun.
Nice work. One question, though: won’t comparing FIP and xFIP yield similar results? (I’m not sure about this, just wondering.)
Good question. Since both FIP and xFIP are rate stats, taking the difference would yield another rate stat. IE a stat that is invariant of the volume one has pitched. I expect it would be proportionally related to HR/FB rate for the pitcher. This stat, however, will increase as a pitcher gets more fly balls outs versus expectations. So if a pitcher is able to sustain a whole season full of fly ball outs while allowing only a few home runs, he would build up a very high CAIN, but if he does it over just one month it would be quite a bit less.
Gotcha