“What makes a man, Mr. Lebowski? … Is it being prepared to do the right thing? Whatever the cost? Isn’t that what makes a man?”

I know how that exchange ends, and you probably do too. Perhaps the Dude’s response to the other Jeffrey Lebowski, the millionaire, was, indeed, right. But maybe there’s something else — something I’ve concocted to make myself feel better. Perhaps what makes a man is the capacity to admit he is wrong.

I was wrong. About Jeremy Hellickson, specifically. In late April, I pegged Hellickson as someone who would regress in his strikeout rate (K%) based on his zone contact rate (Z-Contact%). Technically, I was right — Hellickson’s 75.7% zone contact rate as of April 24 has converged almost all the way back to his career rate of 84.6% (it currently sits at 83.1%).

It’s the change-up I was wrong about. Hellickson’s change-piece posted some filthy outcomes through the end of April. I claimed nothing about the pitch changed. I looked at velocity and movement. I didn’t look at location. Hellickson is spotting the ever-loving crap out of his change-up, and it has worked wonders for him.

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Early last season, I introduced an equation that calculates a hitter’s expected isolated power, or xISO. Since I haven’t discussed it all so far this season, and we’re halfway through June, I figured now is better than never.

Before I proceed: Andrew Dominijanni expanded on my research about a month ago. He incorporated exit velocity, sourced from the new Statcast data hosted at Baseball Savant. The model better explains the variance in the data and has slightly better predictive (year-to-year) qualities, making it the optimal choice.

Andrew’s version of xISO generates a pretty simple calculation, but I’m feeling especially lazy today, and I can find hard-hit rate (Hard%), pull rate (Pull%) and fly ball rate (FB%) all on FanGraphs’ batted ball leaderboards.

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It’s not like we need to talk about Jonathan Villar. We have all seen what he’s doing. But when a guy seemingly comes out of nowhere to become a top-10 fantasy player, it’s usually a big deal. What gives? Who cares. We’re here now. Let’s talk about Jonathan Villar.

Villar is on pace to hit 13 home runs, steal 60 bases, and bat .292. That’s 2014 Jose Altuve, but more power and less batting average. We’ll check the validity of all those paces in a second. The middle one is really not open for much contention, though. It took 16 games for Villar to steal his first two bases this year, but he hasn’t gone more than five games since without successfully swiping a bag. With 21 steals in the 45 games since April 23, he’s basically taking an extra base every other day. Billy Hamilton who?

Neither the speed nor power should have caught any of us by surprise. All of it is well-documented, dating back to 2014. Blake Murphy gave Villar his due back then, noting a 10-homer, 30-steal, .250 hitter is “immensely valuable” given the paucity of talent at shortstop. That has obviously changed this year, what with Corey Seager and Francisco Lindor and Carlos Correa and all that jazz. (Despite their presences, Villar still holds his own.)

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Jeff Sullivan wrote about Matt Shoemaker last week, being one of the first (to my knowledge) to note that Shoemaker had recently ramped up the usage of his splitter. I’m reluctant to overdo it, but you should read that first. I’d also like to borrow one of the main points he made in order to better establish my narrative. I hope you don’t mind.

Sullivan noted Shoemaker’s increased use of the splitter in all counts. Which is great, because it’s arguably his best pitch. His slider is good, too — both induce an almost-equal percentage of whiffs per swing — but it’s the splitter that has coerced a meager .117 isolated power (ISO) in his Major League career. That’s a big part of it. More splitters means fewer other things, and those other things, as Sullivan noted, have generally been bad.

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Previous rankings:
March/April (Preseason)
May

* * *

The more I do this, the harder it gets. Each month I struggle with shedding my preconceived notions of a player’s value and coming to grips with the performance we have actually observed. And then there’s the additional element of teasing out what’s real and what’s not. Occasionally, there’s no change. That makes it easy. But for the guys who have made strides or taken big steps back — that makes it a bit harder. And then there’s accounting for over- and under-performance. Trying to anticipate when regression will occur, if at all, makes my head hur.

Also, there are just so many outfielders. And so many of them seem to be performing at a high level this season. It can be excruciatingly difficult to tease them apart. At a certain point, we’re splitting the microscopic hairs that grows on regular hairs. Full tiers become indecipherable blobs.

You know the rules, but if you don’t: hitters are pretty fluid within tiers. It’s not feasible to talk about every single guy, so feel free to ask questions (or leave criticisms) in the comments. (I know I left off a lot of hitters who make up the shallow side of a platoon or ride the pine. ) If I omitted a legitimate someone, let me know; unless it’s a part-time guy or a prospect, I probably just forgot. It happens from time to time.

I love Bob’s Burgers, so I’m going to name the tiers by my favorite episodes of all time. Because I can! This is off the top of my head, though, so I’ll probably screw up my own list. Oh well. Fight me!

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Updated Feb. 25, 2017

Aug. 16, 2016: Updated Alex’s xBABIP equation and added Andrew Dominijanni’s xISO equation.
May 23, 2016: Published.

Jump around in this post:
Hitter metrics: xBABIP | xISO | xHR/FB | xOBA | xK%
Pitcher metrics: xHR/FB | xLOB% | xK% | xBB%

* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *Do you frequently use RotoGraphs’ “X” (expected) metrics? Do you wish they were easier to find? Have you ever commented to ask if they could be added to the leaderboards or at least wished they were all located in one spot? If so, you may want to…

BOOKMARK THIS PAGE!

I don’t know if there will ever be a time when FanGraphs has a leaderboard devoted to “X” metrics. The fantasy analysts at RotoGraphs have taken a largely vigilante approach to creating descriptive and predictive expected metrics over the years. Moreover, each metric typically undergoes an iterative process by which we improve it when new data is made publicly available to the authors.

So, this is it. This is my best attempt, on behalf of RotoGraphs’ staff and at the polite and enthusiastic behest of its readers, to centralize the freshest versions of the relevant metrics the RotoGraphs staff most frequently cites. I have also built primitive Microsoft Excel-based calculators for some (but not all) of the metrics that crunch the numbers as long as you provide the appropriate inputs. It should save us all an extra minute or two and preserve our sanity a little bit.

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So, Jackie Bradley Jr. hit another home run last night. It’s his seventh of the season and his sixth since May 5. That’s six home runs in 13 games to go with a .404/.474/.762 line. All the while, he extended his hitting streak to 24 games. It’s pretty crazy. He’s on a tear, for sure.

But I’ve seen some overenthusiastic Tweets about his breakout being legitimate. That, I don’t fully understand. He doesn’t seem like a fundamentally different hitter than the JBJ we saw in 2013. Or 2014. Or 2015.

Obviously, the .271 ISO (isolated power) is impressive for a relatively tiny dude. It’s not far off his .249 ISO from last year, so it looks like it might be something sustainable. His strikeout rate (K%) is way down, too, which is undoubtedly a boon to his triple-slash line. But red flags abound with JBJ, all (or most) of which I will detail here.

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I mean, it’s not that surprising. It’s the only outfield with a Giancarlo Stanton, which would be enough to elevate any outfield out of the cellars. It has a Christian Yelich, too, who hits the ball hard but had been somewhat of a fantasy disappointment, having failed thus far to live up to any kind of power potential he once had.

Still, the Marlins are the game’s second-best offensive outfield, per wRC+ (weighted runs created). That’s kind of surprising. I mean, we knew the Pittsburgh Pirates’ outfield, which currently ranks first, would be good. And we probably thought the Chicago Cubs’ outfield, with all its talent and depth, would generate solid offensive numbers, but they’re only 10th.

While it’s a feel-good story riding on the high of a finally-vindicated Marcell Ozuna, it doesn’t look entirely sustainable. But it doesn’t mean we can’t dream, and there are some reasons to be optimistic about the already-established Stanton and Yelich as well as the still-young Ozuna.

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I already wrote about Aaron Nola this year. So, too, have Eno Sarris, August Fagerstrom and Jeff Sullivan. He’s been a big deal.

When I wrote about Nola — barely a month ago, at this point — he kind of took the backseat to rotation-mate Vincent Velasquez, who had recently struck out 16 hitters in a dominant complete game. However, since VV’s first two starts, during which he struck out a combined 25 hitters, he hasn’t struck out more than six hitters in a single game and has shown lapses in command.

Meanwhile, Nola has, somewhat quietly, turned in one of the season’s best first six weeks. He ranks third in pitcher WAR (wins above replacement) behind Clayton Kershaw and the underrated Jose Quintana. But WAR is partly a function of playing time, so this might be an unfair comparison for, say, Kyle Hendricks, who has started two fewer games than Nola.

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When Dylan Higgins invited me on to the Field of Streams podcast last week, he asked me what I typically like to write about. My answer was an incoherent, stammering mess, but the gist of it was I like to write about all sorts of things. The trajectory of my writing has changed a lot over time.

I think I originally wanted to write primarily about market inefficiencies in fantasy baseball. The constant instantaneous misvaluation of players fascinates me, and effectively exploiting these inefficiencies make champions. Occasionally, I return to this topic.

That occasion is today, and today, I’m in the mood for blind résumés. I cherry-picked some stats for three players, whose names I stripped away, and I want you to decide, before reading any farther, in which order you would take these players.

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