Man, I am having a blast with the Baseball Info Solutions batted ball data that was recently added to the batted ball leaderboards. Sure, there are reasons to complain: the batted ball spray and contact quality statistics lack context, leaving you in the dark about how spray and contact intersect. For example, there’s Hard%, and there’s LD%, but how many of a hitter’s balls in play are hard line drives? (You can actually find this data on individual player pages under the “Splits” tab — just not on the leaderboards.)

Just because the available data aren’t as granular as one might wish they were doesn’t make them worthless or unusable. Yesterday, I demonstrated that we can still achieve small gains in our understanding of batting average on balls in play (BABIP) using the new data.

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You may have noticed that FanGraphs now feeds batted ball data, courtesy of Baseball Info Solutions, into its leaderboards. The day the data appeared, my mind buzzed with ways they could be useful in improving our understanding of a hitter’s batting average on balls in play (BABIP).

Mike Podhorzer already augmented previous attempts at devising an equation for expected batting average on balls in play (xBABIP) for hitters by incorporating elements of a hitter’s power, speed, plate discipline and batted ball tendencies. So, with fresh numbers in hand, I embarked on a journey to further improve the ever-evolving xBABIP. However, I sought to do so by using only batted ball data. Basically, I intended to develop a convenient xBABIP equation, one that can be computed using almost entirely variables found on the same page.

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NL OF Tiers: March (Preseason) 2015
Also, David Wiers’ AL OF Tiers: May

This is my second ever installment of tiered rankings so, I admit, I’m still figuring out how to properly balance a hitter’s present and future values. It’s too easy to rank them by, say, their current ESPN Player Rater rankings, but it would be foolish to still rank them simply by expected end-of-season value, as I did in March.

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Let’s cut straight to the chase. Take a look at the statistical snapshots below:

Obviously, Player 1 is benefiting from a higher batting average on balls in play while Player 2 is getting burned a bit by his. Still, take away their triple-slash lines (but leave the isolated power) and you have two players with almost identical numbers, down to the six steals on eight attempts and the meager isolated powers (ISOs). Where they differ a bit is in plate discipline: Player 1 has a much healthier walk rate than Player 2 and a couple fewer strikeouts. So while Player 1 is benefiting from the a higher BABIP, he can also reasonably be expected to post a marginally higher batting average and noticeably higher on-base percentage. Most importantly, the two hitters are eligible at the same position and are, thus, substitutable.

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It’s hard to believe the current incarnation of Curtis Granderson could show up, by default, at the very top of any FanGraphs leaderboard for positive reasons. Yet there he is: the Grandy Man leads all National League outfielders in chase rate (O-Swing%), at 16.7 percent. Only Brett Gardner and the fabled Joey Votto have offered at fewer non-strikes than Granderson among qualified Major League hitters.

Granderson has seen 128 pitches outside the strike zone. Of those pitches, he has swung at 21 of them. And of those swings, he has made contact with 17. For the mathematically disinclined, that’s a grand total of four swings and misses on pitches out of the zone. That’s the fewest of any hitter who has seen at least as many pitches as Granderson has.

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Chris Carter is off to a bad start. This is an unambiguously true fact. Jeff Sullivan, among other Twitterers (Tweeters?), have succinctly illuminated this unambiguously true fact:

selection of players with ISO of .000 Curtis Granderson Brandon Phillips Desmond Jennings Logan Morrison Chris Carter

— Jeff Sullivan (@based_ball) April 21, 2015

Carter has supplemented the zero extra-base hits with four singles, 21 strikeouts and nary a run batted in to speak of through 51 plate appearances. (FYI, that’s a 41.2-percent strikeout rate.) His atrociously bad start is the talk of the Twitter town, and it has Astros Manager A.J. Hinch dropping him in the batting order. As of last night, Carter’s ownership had dropped to 67.7 and 73 percent in ESPN and Yahoo! leagues, respectively, as owners have jumped ship.
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If fantasy baseball were a marathon, we’d all have run about a mile and a half. Most races don’t even have their volunteers stand with trays of water cups this early on, so you’d better pace yourself if you’re already tired. I think I forgot to stretch.

Here’s an obligatory sentence reminding you about the caveats about small samples while attributing a shred of validity to them. OK, now that the formalities are out of the way, let’s talk ownership trends. National League outfielders are a promising bunch, especially in regard to the youth movement. I’ve been sold on a handful of them prior to the start of the season, and I’m surprised by their meager ownership numbers. They aren’t completely unowned, as my misleading title alleges, but they’re close enough.

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Last week, I identified potential stolen base streamers for daily fantasy leagues and weekly leagues with daily transactions and lineup changes. I used a pitcher’s career caught-stealing and pick-off rates as criteria to determine if a particular matchup was primed for streaming a speedster with the hope of him stealing a base (or two or four).

I like how it turned out, but it felt hastily constructed. A pitcher’s career rate seemed too broad a scope, especially considering the possibility that a pitcher can get better (or, perhaps, worse) at limiting steals and picking off runners over time.

With a little more time and care, I fleshed out everything a bit more and added an additional criterion: catcher effectiveness, which can be most obviously measured by caught-stealing rate. But I think there also is merit to calculating the frequency at which runners attempt to steal on a catcher. In a sense, it measure runners’ perception of a catcher’s skill, especially for those at the tails of the distribution.

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I’m really not privy to the whole daily fantasy baseball thing, as proctored by FanDuel or DraftKings. It’s probably good that I’m not because I’m 98 percent certain I would immediately fall in love with it.

Still, I’m intrigued, mostly because it takes streaming to the extreme. And I love streaming. It’s a tedious, somewhat painstaking process, what with combing through splits, looking for the juiciest matchups that are also cost-effective.
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Did you draft Dustin Pedroia, who is on pace for almost 300 home runs? Mookie Betts? In a fit of extreme homerism, the entire Red Sox lineup, which will surely score 1,296 runs? That must feel pretty good. Good for you, Pete. Give yourself a pat on the back.

Or, wait — you were the one who drafted Kyle Lohse, weren’t you? Threw a mid-round pick at Mat Latos? Wrote “stream Nate Karns” on your list of good Tuesday decisions? Do you regret it?

Man, there have been some truly brutal starts to kick off the season. It’s really easy to make a knee-jerk decision in reaction to such preposterous, ego-damaging, season-dooming starts, but you have to remember — and I think it goes without saying — that these guys will (probably) never be worse this year than they were today.

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