Challenge: Prove Brandon McCarthy’s HR/FB is Not Bad Luck

In two starts spanning 12 innings, Brandon McCarthy has allowed six home runs. Out of 12 fly balls. For a 50% HR/FB rate. After witnessing the last of those homers in Monday’s game, I Tweeted about it. Because that’s what all the cool kids do nowadays, Tweet, right? After a couple of back and forths, I then Tweeted the following:

I stand by that statement. We’ve come a long way in the past decade in understanding pitcher performance. With the introduction of PITCHf/x, we know far more than we have ever known before. But there still remains a wealth of knowledge that I wish we had.

When Voros McCracken first introduced the world to DIPS, most understandably scoffed. Eventually us statheads embraced his ideas and metrics such as FIP that were built upon those ideas were created. Then when we discovered that a pitcher’s HR/FB rate was quite flaky from year to year, the xFIP metric was developed. With all these metrics drilling into our heads that this is what a pitcher’s ERA should be absent luck on balls in play and sequencing randomness, we perhaps went too far, believing that any difference between a pitcher’s ERA and DIPS ERA is due to good/bad luck. Now, it has become trendy to acknowledge the luck component, but then side-step it and try justifying the out/underperformance.

The problem with this is that there is never any evidence provided to support what the scout in you supposedly sees. You say that Pitcher X throws too many meatballs? Okay, prove it. Cite facts, data, evidence. Compare X’s meatball percentage to every other pitcher. Is it actually higher? Do his meatballs get launched for homers more frequently than other meatball throwers? If so, why?

Without this research, you’re just succumbing to confirmation bias. Rather than diving into the problem without any preconceived notions, the analyst points to an inflated (or suppressed) HR/FB rate as the evidence that a pitcher is “too hittable”, “throws too many strikes/around the plate too often” (my favorite) or whatever description is decided upon. An inflated HR/FB rate on its own cannot be the evidence. How do we know that it’s not bad luck?

McCarthy’s unfortunate start is simply the continuation of his struggles with the long ball that began last season. His 16.3% HR/FB rate easily led all qualified Major League starters. But consider this — before last year, McCarthy’s career HR/FB rate sat at 9.3%. That actually rates below the league average.

So if you lean toward McCarthy lacking the skill to prevent home runs on fly balls, then what has changed since 2013? It’s true that McCarthy is actually a very different pitcher now. But his transformation should have boosted his ability to prevent fly balls from leaving the park, not reduced it. He has morphed from soft-tossing flyballer into a hard-thrower with a ground ball tilt. And fastball velocity is negatively correlated with HR/FB rate. So any argument that McCarthy’s new found velocity is increasing the opposing batter’s speed off the bat, resulting in more homers, is a flawed one. Maybe you think his hotter heat is straighter than it used to be and straighter fastballs lead to more homers? Okay, fine. Interesting hypothesis. Go test it!

Now let’s get this out of the way. I am by no means suggesting that I naively believe any pitcher whose HR/FB rate deviates from the league average is lucky/unlucky. I’m merely conceding that although luck could be the primary culprit, perhaps it’s a difference in skill. I just don’t know for sure. No one knows.

Clayton Kershaw owns a career HR/FB rate of just 6.7%. We all know he is the best pitcher in baseball and has been a member of the elite for many years now. But what about Chad Billingsley? In 1,175.1 innings, he has posted a suppressed 7.6% mark! Both have called Dodger Stadium home their entire careers, but sport nearly identical home/road splits, so it’s not a ballpark thing. Clearly in over 1,000 innings, the possibility that luck plays a major role is severely reduced. So it’s obvious that some pitchers do seemingly have the skill to limit home runs on fly balls, while others don’t. But how do we measure, quantify and understand it? How do we know?

So I am issuing a challenge:

Prove that Brandon McCarthy’s HR/FB Rate is Not Just Bad Luck

I am admittedly devoid of the necessary skills to research this on my own. I wouldn’t even know where to begin. So dive on in and share your findings. Any claims you make should be supported by facts. Even if you come to the conclusion that it is all bad luck, I want to know!

For those that accept my challenge and perform the research, send me an email (in my signature). I will publish a follow-up and share anything interesting so we could continue this discussion. It’s your chance to see your name in lights in a FanGraphs article!





Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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Brad Johnsonmember
9 years ago

First hypothesis: GB / FB Splits (see yesterday’s Daily Grind)

Fly ball hitters account for the majority of home runs, and they hit better against ground ball pitchers. Like Mike, I don’t have the database skills to verify this. I’m pretty sure it’s the answer, although there might be a slice of bad luck baked in too.

Brad Johnsonmember
9 years ago
Reply to  Brad Johnson

To clarify, I should say I’m pretty sure it’s part of the answer. There are probably competing effects. McCarthy is definitely reaching the point where his elevated HR/FB looks like a skill rather than noise.

Brad Johnsonmember
9 years ago
Reply to  Mike Podhorzer

I’m suggesting his profile is inordinately good for fly ball hitters. He doesn’t have to face an above average rate of fly ball hitters for this to be part of the answer/problem.

Nick
9 years ago
Reply to  Dolemite

There is selection bias going on here; if you’re a FB pitcher and have a high HR/FB rate, you’re not going to be in the league very long.

Dolemite
9 years ago
Reply to  Dolemite

Nick That is survivorship bias, and you are certainly right

Kris Gardham
9 years ago
Reply to  Dolemite

I agree with this as much as I can, given the question. Although, I think it’s probably a result of the second part of your answer, or the evidence, rather. From this point on, just preface everything I say with, “I think….”

Basically, it’s not the batted ball tendency, it’s the pitches thrown to get the batted ball and their placement.

When you look at the guys that generally perform poorly in this regard over the long haul, you’re looking at guys with a fastball/two-seam/sink repertoire. I would imagine that this also has a lot to do with why velocity correlates to HR/FB — A lot of these guy’s FA’s are really just FT or SI that are borderline.

Maybe if you query “borderline” FT/SI’s you’ll find a correlation. The problem with that is, if you just query FA, there’s so many of them, you won’t find anything. And if you query FT/SI all together, you’re probably not going to find much of anything (although i bet you find at least something) — so if you query fastballs with like, i dunno, 4-8 vertical, and maybe 7-10 horizontal?

Honestly, I’m sure the best way to do this is to just take the guys with sustained high HR/FB rates, and plot their fastballs (that resulted in a flyball if you want) on the standard pfx movement graph, and highlight dingers.

My guess is that there’d be at least some grouping in that inbetween zone.

wildcard09
9 years ago
Reply to  Brad Johnson

I knew this brought to mind a recent THT post, and here it is:
http://www.hardballtimes.com/batted-ball-trajectory-splitting-the-difference/

Shane didn’t look at HR rates there but he found that while FB hitters do produce higher liner rates against GB pitchers, they actually produce lower than average FB rates of just around 30~31%. And they produce slightly above average GB rates. So essentially they turn some classified FB into liners, which means better contact, but without further information on these liners it’s impossible to know whether it resulted in more HR or not.