Funny how we have not written much at FanGraphs about Robbie Ray this season. Eno Sarris lauded Ray’s velocity in brief in the spring; in July I expressed enthusiasm in Ray but didn’t give him the most glowing recommendation; all of which finally culminated with August Fagerstrom’s piece two-and-a-half weeks ago declaring Ray MLB’s newest strikeout madman. That actually seems like a lot of coverage, now that I mention it all, and it kind of is. But it’s all more recent and probably deserved to happen sooner, especially since Ray has posted a strikeout rate of 9.6 K/9 or better in every month this season.

Sarris noted that Ray is mostly a two-pitch guy, thereby dampening his value. Fagerstrom uncovered related weaknesses during Ray’s third trip through the order, likely correlating negatively with his lack of variety. Then again, Fagerstrom acknowledges how big a role sequencing plays in a pitcher’s success, and Ray has been woefully unlucky in this regard, forcing the split between his ERA and FIP (E-F) wide open.

Let’s play pretend. Let’s say Ray never develops a third pitch. Let’s say Ray rides the status quo through next season. Would that be so bad? Probably not, because Ray is doing his best Yu Darvish impression (sound familiar?):

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If I had a dollar for every time I used this lede, I’d have, what, like, four dollars? I can’t help myself. Blind résumés are my jam because so much of how we value players is tied up in our biases and preconceived notions. Alas, Starling Marte and, of all people, Hernan Perez make for excellent comparisons when prorating their 2016 stat lines. Per usual, I won’t tell you who’s who:

Did you figure it out? The home run column gives it away, given Perez (Player B) has hit more home runs than Marte (Player A) in about half as many plate appearances. Outside of that, we’re looking at mirror-image power, stolen base rates, and plate discipline, the latter of which is most fascinating to me. We’ll dig into the weeds in a bit here — Perez has some faults we ought to acknowledge — but for all intents and purposes, Marte and Perez are nearly-identical, very-elite options through the end of September. (Last week I mentioned this — that Perez could be a top-flight outfielder from here on out — and, frankly, I’m surprised I got virtually no push-back from readers.)

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Previous rankings:
July
June
May
March/April (Preseason)

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Last month, I asked what you all wanted from rankings. A few responded with answers I expected: rankings should reflect rest-of-season performance, informed by past performance. It seems almost silly I even asked in the first place. The reason it came up is because I think fantasy owners occasionally underestimate how impactful a month or two of extreme regression can be. It makes it especially difficult to rank someone like Marcell Ozuna circa June 1: he had a monster BABIP (batting average on balls in play) through May, and while he flashed still-legitimate power, we could reasonably expect the batting average to fall.

Like clockwork, it has. Ozuna’s BABIP by month: .281, .459, .284, .280. May was the obvious outlier in which all of Ozuna’s good fortune on balls in play was concentrated. The isolated power has, too, somewhat predictably, dipped since then. Ozuna wasn’t even a top-60 outfielder in July. Such is the nature of small samples. And yes, two months of baseball is still a fairly small sample. Joey Votto was batting only .249 through June 30. Then July happened, and now he’s batting .293 with about 20 more runs and RBI apiece (as well as a dropped foul ball).

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If you follow me on Twitter, you know how this ends. Statistically speaking, though, you probably don’t follow on me Twitter, so you probably don’t know how this ends. Then again, maybe you really do know how this ends, because when you clicked this link, you probably had to read the title first. Or maybe you didn’t! Honestly, I don’t want to pigeonhole you. Maybe you’re the kind of person who clicks links all willy nilly with zero regard for content. I’m sure SEO folks love you but also lose their minds trying to understand you.

No matter. Let’s pretend you didn’t read the title. Now you’re presented with blind résumés. Can you guess who Players A and B are?

Did you have to cheat? It may actually be more difficult than you thought. You know the names already, but perhaps you got them out of order: Kyle Hendricks is Player A and Tanner Roark is Player B. But look at that! Hendricks and Roark are almost perfectly identical within every metric. Roark even edges Hendricks in xFIP, innings per start, and WAR per start. It’s kind of a big deal, given Hendricks is owned in more Yahoo! leagues than Roark (85% to 78%).

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Purposes of this post:

1. Glass half-full: To update a year-old xBABIP equation that estimates a hitter’s batting average on balls in play (BABIP) based on his batted ball data;
2. Glass half-empty: To pay restitution to readers and beautiful human Mike Podhorzer for damages incommensurable, wrought by the careless oversight of the initial version of the equation;
3. Regardless, a glass with some amount of water in it: To provide, for those lacking attention or care, the updated version of equation aforementioned, found here for one’s immediate gratification sans linguistic obstruction.

An Explanation

Last year, when FanGraphs obtained Baseball Info Solutions (BIS) batted ball data, I was, in a word, jazzed. Kind of like the Statcast revolution now (but not nearly as popular or flashy), FanGraphs in conjunction with BIS bestowed upon the sabermetric community more great tools to describe and predict player performance. I developed an equation to estimate a hitter’s expected batting average on balls in play, or xBABIP. This was not an original idea — other iterations of xBABIP already existed — and I freely admitted then (and now) that my equation was not necessarily superior to any other. My equation simply offered new value by (1) using the new batted ball data and (2) incorporating metrics from a single, easy-to-locate source to make easier the calculation of the equation.

Unfortunately, the equation has long been overdue for a makeover — right from the very start, basically. See, in my attempt to create a relatively simple equation, I overlooked a critical element of the data that has produced imperfect xBABIP estimates. In an attempt to make this a learning experience for anyone who cares, let’s take a look at batted ball data by season at the league level.

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A pitcher’s excellent performance early in the season can obscure poor performance later on, as his stats slowly converge toward expectations. If you held onto Jordan Zimmermann too long, you suffered the consequences. The same applies for the opposite scenario; Matt Shoemaker has been one of the baseball’s better pitchers since mid-May after an atrocious start to the season.

Alas, the deeper we get into the season, the more important it becomes to check recent leaderboards. With the way player performance ebbs and flows during a season, a span of five or six starts can probably be considered a small sample size. Still, keeping an eye on these small samples can illuminate interesting trends.

For whatever reason, there seem to be a lot of unfamiliar or unexpected names on FanGraphs’ xFIP leaderboards under the “last 30 days” split. Let’s break them down!

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Previous rankings:
March/April (Preseason)
May
June

* * *

To this day, I think I don’t fully understand what y’all want. With these monthly rankings, do you want end-of-season rankings or rest-of-season rankings? For the record, given we just eclipsed the halfway point of the season, end-of-season rankings would equally weight players’ first and second halves. Rest-of-season ranking, meanwhile, would unequally weight a player’s second half in favor of his first half. First-half performance informs second-half rankings, but more in the sense that “regression will hit this guy hard” and so on.

I ask because, man, y’all rip into us pretty good with these rankings sometimes. And I know I’ve failed to adequately communicate my criteria for ranking particular players a given way because I simply don’t have enough words or time.

With that said, I will provide for you here rest-of-season rankings for National League outfielders, complete with anticipated regression and all that. Tiers will be named in order of my favorite Every Time I Die albums, which is totally not obscure in any way. Enjoy! (Or not.)

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Forgive me for some recycling some of last week’s introduction:

Back in March, I made some bold predictions, as all RotoGraphs staff do. Some bold predictions I make simply for the sake of being bold. Or for the sake of making a prediction. One of the two.

We don’t all review our bold predictions — some of us, like Mike Podhorzer, like to wait until October. Some of us don’t have the discipline for such delayed gratification. And, I speak for the group, whether they like or not, but all of us forget most our bold predictions anyway. I remembered a couple, but looking back on them — man, sometimes I wish I hadn’t.

Enough talk. Let’s dig in.

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Back in March, I made some bold predictions, as all RotoGraphs staff do. Some bold predictions I make simply for the sake of being bold. Or for the sake of making a prediction. One of the two. But I don’t have a vested interest in my predictions, mostly because (1) they typically suck and (2) I don’t own many, if any, shares of the subjects of my predictions (because, well, the predictions suck). It’s kind of like not putting your money where your mouth is.

In this case, I absolutely have a vested interest in Jose Ramirez. Chris Mitchell and I both hold a special place in our hearts for him. I’ve come to realize, in my years of watching and loving baseball, that I most appreciate the hitters who are (debatably) underappreciated contact hitters. Victor Martinez. Pre-breakout Daniel Murphy. Nick Markakis. Martin Prado. Reggie Willits???

Speaking of Prado, Ramirez looks like peak Prado right now, and in more ways than one:

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I cover the National League outfield beat, but I occasionally abdicate my duties. I’m easily distracted. I also enjoy constructing narratives from a player’s statistics, and being on the NL outfield beat, I can only cover the same dudes so many times. But it truly has been a while, and given that market inefficiencies will always plague player valuation, I hear an old go-to of mine calling my name.

I’ll offer three NL outfielders at varying level of ownership (per Yahoo!’s tallies), make a case for each, and offer names of other more-owned NL outfielders to drop (or trade, given their inflated perceived values) in place of them. Got it? Cool. Let’s get cracking. (Ownership rates are current as of June 27.)

Less than 60% owned

Melvin Upton Jr., SD
58% owned

I do not totally get this, but I also do totally get this. Upton was bad for a while. The last three years were difficult to stomach, with his volatile offensive profile finally succumbing to his poor contact skills. The strikeouts grew, and the power shrank, and Upton was but a shell of his former self. He left a bad taste in our mouths.

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