Archive for 2017

Playing time can make or break a baseball player’s fantasy value. An elite player may not finish above replacement level if he suffers an injury and plays only half the season, and a lackluster player could finish above replacement level simply by playing every single day. This is all intuitive, and the fantasy community generally approaches these kinds of things rationally. In other words, most players are appropriately valued, outside of the market inefficiencies that inevitably warp player values.

One-dimensional speedsters — dudes who steal a bunch of bases and do little else — are much harder to peg. Their value is tied up primarily in one category, as stolen bases (SBs) do not directly correlate with other categories the way home runs would with runs and RBI, for example. The issue becomes all the more confounding when one considers the contemporaneous scarcity of SBs relative to home runs. There’s more to value than just SBs and plate appearances (PAs), but the fact of the matter is the two statistics by themselves correlate very strongly with a player’s end-of-season (EOS) value (which, here, are informed by Razzball’s Player Rater).

In the last five years, baseball has seen 75 player-seasons of 30-plus SBs — 15 steals a year on average, a trend that didn’t fundamentally change in 2016 (although that doesn’t mean SBs aren’t scarce). A simple linear regression of SBs and PAs, the latter of which serves as a proxy for other counting stats such as runs and RBI, against EOS value produces a remarkable 0.71 adjusted R²:

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The fantasy community is down on Justin Upton. I get it, but it’s a little strange to me given our collective penchant for recency bias. Upton had a monster second half and finished the season an almost-perfect replica of his usual self. (The operative qualifier being “almost.” We’ll get to that in a second.) Sure, it was a rocky year, but hey, Joey Votto had one, too. Dude was batting .213 with a 27 percent strikeout rate (K%) through May…

Right, so Upton was an almost-perfect replica of himself. In a vacuum, his production looks nearly identical to his typical annual accomplishment, down to nearly every statistic except for his batting average on balls in play (BABIP). In my investigation of his woes, I noticed his uncharacteristically low infield hit rate (IFH%). Here’s a list of hitters with higher infield hit rates than Justin Upton in 2016:

• Salvador Perez
• Kendrys Morales
• Albert Pujols
• One hundred and thirty five other players not surnamed Ortiz, Mauer, Seager, Granderson, Cabrera, Votto or Kemp

Yes, Upton ranked among the bottom 6 percent of hitters in terms of infield hits. If there’s a single bone to pick about Upton’s season — well, aside from the insane volatility — it’s that his BABIP failed to get back on track, continuing to linger at a league-average mark. It seems a trend has emerged; accordingly, it’s easy to accept said trend as a new normal, as a resignation of Upton’s fifth tool.

I’m here to make the classic* Infield Hit Rate Defense, or IHRD, as it’s known in the infield hit community.**

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Robbie Ray is already shaping up to be one of 2017’s most contentious starting pitchers headed into draft day. (This isn’t even my first time writing about him in the last half-year.) His 28-percent strikeout rate (K%) and 3.45 xFIP scream of an elite starter, but his 4.90 ERA and 1.47 WHIP, sustained during more than 170 innings pitched, seem to say otherwise.

Analysts and laymen who have expressed optimism about Ray have done so in regard to his alleged hittability. That 1.47 WHIP didn’t come from nowhere: his .352 batting average on balls in play (BABIP) got him there. You’ll hear a variety of arguments: he struggles on his third time through the zone; he lacks a quality third, or maybe even second, pitch; and so on. I’m not here to argue the validity of those sentiments.

I want to talk exclusively about Ray’s BABIP. Well, his sinker, too. And maybe even his strand rate (LOB%)… But mostly his BABIP. Please, have a seat. I don’t want to fluster you.

Ray’s .352 BABIP in 2016 was the second-worst of the last 15 years. That’s out of 1,281 individual player-seasons posted by qualified starting pitchers. His BABIP was historically bad — strange, you’d think, for a pitcher who has quickly demonstrated a lot of promise. So, I want to approach this whole BABIP thing in a vacuum. Let’s just look at the facts — not even alternative facts, but real facts!

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Around this time last year (edit: actually, it was more like sometime in 2014), Eno Sarris introduced the Arsenal Score. It was, and still is, a novel concept: for every pitcher, evaluate each of his pitches based strictly on their strikeout- and ground ball-inducing tendencies. Each pitch would be evaluated relative to its contemporaries — in other words, Corey Kluber’s slider would be compared to all other sliders in the league.

I’ll speak for Eno when I say the original Arsenal Scores weren’t meant to be especially rigorous. They received some flak for being mathematically inaccurate — to which I say, it doesn’t really matter. Originally, Eno calculated separate Z-scores for the ground ball rate (GB%) and swinging strike rate (SwStr%) — called “Z-BIP” and “Z-Whiff,” respectively, in the results to follow — of each pitch for every pitcher. The aggregate Z-scores — two Z-scores times X number of pitches — comprise the full Arsenal Score.

This time around, I propose a few tweaks:

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There are plenty of ways to characterize David Phelps‘ success in 2016. Among pitchers who threw at least 80 innings, he posted the 5th-best ERA (2.28), 6th-best xFIP (3.15) and 7th-best FIP (2.80). That’s a big deal, although it’s a decidedly smaller deal considering the bulk of Phelps’ innings came from the bullpen.

The reason for Phelps’ success — the cause to the effect, that is — is fairly obvious:

Phelps added more than 3 mph to his four-seamer and sinker as well as a tick or two to each of his off-speed pitches.* In an August edition of his NERD game scores, Carson Cistulli quipped, “As with most other pitchers, Phelps at 94-95 [mph] is markedly different than Phelps at 91.” Indeed, Cistulli. Phelps looked like a changed man.

It’s easy to attribute his sudden late-career success to his almost-full-time move to the bullpen. It’s how the narrative typically plays out: a pitcher’s velocity plays up better in short spurts. It’s why we expect failed starters can become elite relievers. It’s a cognitive bias, but it’s a bias we have because it tends to be true. This shorthanded logic, however, undersells Phelps’ gains both under the hood and on the mound.

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I’ll lead with a series of questions: What’s the preferred way to analyze a mock draft? Would you rather read about the writer’s breakdown for his or her specific draft results? Or breakdowns by position? Of each owner’s team?

I plan to take the former-most approach here in regard to the Too Early (#2Early) Mock Draft, as curated by Justin Mason and graciously hosted by Couch Managers. A 15-team slow draft that began as soon as the season ended, I did not hesitate to vocalize my discomfort in drafting, even in the spirit of mockery, with absolutely zero planning.

Alas, that’s the fun of the Too Early mock (or so David Wiers tried to convince me): just wing it. Or see what happens.

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I’m an Alex Dickerson fan, but I don’t know if anyone else is. He at least appears to have gone largely without fanfare thus far, as evidenced by his lowly ownership rates (4.7 percent at ESPN, 5 percent at Yahoo!). He never projected to be much of anything; former FanGraphs prospector Kiley McDaniel graded Dickerson’s tools below-average across the board, with exception to his plus raw power, and Dickerson led a weak crop of Padres prospects prior to the 2015 season in terms of projected WAR.

Fast forward to 2016, and Dickerson doesn’t look so meager. In 240 Triple-A plate appearances, he generated the Pacific Coast League’s 3rd-best wOBA. In fact, it eerily resembled that of the lauded Willson Contreras, and it only trails by a nonzero margin that of the seemingly powerful Mitch Haniger. Dickerson not only cranked up the power, posting a career-best .240 isolated power (ISO), but also shaved more than 7 percentage points off his strikeout rate (K%). The hit tool that once graded out well-below-average suddenly looked like a solid asset. While some hitters sacrifice power to refine their plate discipline or contact skills, Dickerson’s 3-year ISO of .199 from 2013-15 increased about 40 points.

The best news is the gains have carried over to the Major League level. To attest, Dickerson’s plate discipline, by definition, is above average:

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