Finding Useful SP Using F-Strike%

Since you read Fan/RotoGraphs, you’re probably in the habit of looking at any number of peripheral stats while searching for your next streamer or roster plug. Allow me to add to the noise as you attempt to talk yourself into taking a chance on certain pitchers, while talking yourself out of others.

You might look at K%, for instance, which is a much better indicator of a pitcher’s usefulness than K/9, though K/9 is a much more common stat in that a number of sites will list it, and is included in lieu of K% on the default leaderboards at FanGraphs itself. Because K% displays strikeouts as a percentage of batters faced as opposed to the number of outs recorded (essentially what K/9 does), it is a better indicator of how efficient a pitcher is at striking batters out.

Understandably, then, K% correlates with IP, W, ERA, and WHIP at a significantly higher rate than K/9 does. Because I am an obsessive baseball lout, like you, reader, I recently explored differences in pitchers’ K/9 and K% just for the hell of it; while the results where not surprising, they were interesting. The results can be found here.1

What was slightly more interesting was when I went started fooling around with F-Strike% and saw how it correlates with certain other 5×5 stats. Generally, it correlates well with those stats, especially WHIP and IP. Eno Sarris explored the effect of F-Strike% on BB% last summer, and found that F-Strike% “explains almost half of the variance in walk rate.” This jives with the -0.401 correlation between F-Strike% and WHIP that I found.1

It should go without saying that even a significant correlation doesn’t completely explain anything, statistically speaking, or predict anything, or indicate a cause-and-effect relationship between the arrays. I didn’t control for other variables (like K%), which would have been useful, but hey, I’m not a computer.

At any rate, simply looking at this years F-Strike% leaders, a number of players pop up who are available in a high percentage of fantasy leagues. The chart below displays a few of said players, with a couple of more widely owned players (Tim Hudson and Tommy Milone) included for comparison. (Does not include Tuesday’s games.)

Name %Yahoo %CBS %ESPN FStr% K%
Kyle Lohse 60.0% 69.0% 44.4% 69.7% 16.2%
Bronson Arroyo 36.0% 61.0% 33.6% 69.1% 14.1%
Kevin Slowey 17.0% 25.0% 5.9% 68.8% 18.1%
Brandon McCarthy 46.0% 58.0% 56.5% 68.1% 14.3%
Tommy Milone 56.0% 84.0% 86.2% 67.8% 20.6%
Tim Hudson 73.0% 87.0% 83.7% 67.8% 18.6%
Ervin Santana 68.0% 59.0% 80.3% 66.4% 20.6%
Jose Quintana 16.0% 57.0% 8.0% 64.7% 18.1%

My favorite here is Kevin Slowey, a graduate of the Minnesota Twins Academia of Walking No One. Unfortunately, he’s also been a banner member of the Club of Perennially Injured Pitchers. His comeback with the Miami Marlins this year has been an interesting one, as he’s posted a K/BB of 3.58 (top 30 among qualified starters) on the strength of a predictably low BB% (5.1). His E-F is worrisome, maybe (20th worst in MLB), and his strand rate is perhaps unsustainable at nearly 84%. But his HR/FB (10.8%) is right at league average (10.9%), and also aligns well with his career average (10.1%), so even given the inordinate number of fly balls that Slowey allows, we needn’t expect his HR/FB to kill him going forward. He consistently pitches ahead in the count, and because of that, might be a decent bet to maintain that negative E-F and help your ERA.

Seeing Slowey among the league leaders in F-Strike%, and knowing that F-Strike% likely has some bearing on those stats which make a pitcher fantasy-friendly, has encouraged me to add him in more than one of my leagues, even despite a couple of underwhelming recent starts. His peripherals compete with those of the rest of the players on this list, yet he is by far the least owned among them.

One of the biggest negatives with Slowey, I suppose, is that he plays for the Marlins and, thus, isn’t likely to see much run support, yielding few Wins no matter how well he pitches. But if you’re in need of a boost in rate stats, or if your league mercifully uses Quality Starts in place of Wins, Slowey’s as good as any of these more widely owned players, and can likely be had for free.

Epilogue: I watched Slowey’s Tuesday night start vs. the Rays in Tampa. He was throwing some first-pitch breaking balls for strikes, but also was getting behind in the count more often than usual (58.3% first strikes) and he was beat more often than not when he had to throw a four-seamer over the plate for a sure strike — two such pitches were smoked for doubles, and he gave up four doubles total.

He did not walk a batter, however, and avoided yard work yet again, so I’m still a believer than when he doesn’t have a game wherein he suffers through a .400 BABIP, he’ll be pretty good.

1 I used a data set of all qualified starting pitcher seasons from 2003-2012 (854 seasons in total) and compared how K/9 and K% correlated IP, W, ERA, WHIP, and K (i.e. the major 5×5 stats, plus IP, which is of interest for other reasons).

K/9 | W K% | W K/9 | ERA K% | ERA K/9 | WHIP K% | WHIP
0.2754 0.3231 -0.4631 -0.5425 -0.4702 -0.5685
K/9 | K K% | K K/9 | IP K% | IP K/9 | LOB% K% | LOB%
0.9277 0.9435 0.1942 0.2502 0.3748 0.4266





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novaether
10 years ago

Semi-related question: do any ERA predictors use FStr%?