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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Yesterday, FanGraphs made public its splits leaderboard, which the authors have been able to test and refine in private for some time now. It’s an incredible tool. If you haven’t checked it out, you should. If you haven’t thanked Sean Dolinar for building it, you should. (If you have any preliminary feedback, leave it in the comments and I’ll pass it along.)

There are a seemingly infinite number of ways to cross-cut data in endlessly fascinating ways. Splits by handedness, situation by outs, situation by leverage, situation by defensive alignment (shift or no shift!) — the list goes on. But the thing that most interested me immediately was understanding the implications of more granular batted ball data.

Two tools I once refined/created — xBABIP and xISO — rely almost exclusively on Baseball Info Solutions (BIS) batted ball data. Yet they were limited in their capabilities because of the limited nature of the data: we knew each hitter’s contact quality (hard/medium/pull) and contact direction (pull/center/oppo) but now how the trios intersected. But, ah, the splits leaderboard.

The following tables depict the batting average on balls in play (BABIP), isolated power (ISO), and home runs per fly ball (HR/FB) in 2016 by each cross-section. Read the rest of this entry »

I’m needlessly competitive. I’ll manufacture any kind of pathetic excuse to turn literally anything into a contest, especially if there’s a moderately easy way to tally stats for it. So, let’s review the RotoGraphs staff’s picks for the 2016 season.

We make picks every season, but as I took up curating them last season, I wanted to hold us accountable while also simply seeing how well we did. Hindsight-spoiler: we actually did pretty poorly. Having not yet evaluated the results whatsoever, I hope for better but secretly anticipate more of the same.

The rules: are dumb and contrived. You’re welcome! Anyway, I choose a winner for each category based on, yes, stats, but also the uniqueness of the pick. For example, picking Noah Syndergaard as 2016’s best sophomore pitcher wasn’t exactly groundbreaking.

Again, this is mostly for fun, but it’s also worth rewarding, with the weakest of praise, those who excelled with their picks. As a reminder, I describe the criteria for each category in the original post. With that said, let’s needlessly compete!

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A little while ago, a bunch of industry dudes participated in a way-too-early slow mock draft aptly dubbed the Too Early (#2Early) Mock. On Tuesday, I dissected the team I drafted with some limited analysis for each pick. Some people find this helpful, entertaining, what-have-you. Personally — and while a particular owner’s strategy is certainly interesting to ponder — I prefer a more macro characterization of the draft.

There are several ways to approach something like this, the most prominent of which, in my mind, being to comb through each round or to comb through each position. I’ll take the latter route here, identifying a “reach” and a “steal” (or plural) at each position.

I rely heavily on my own projections and rankings come draft day. Alas, I must apply a caveat to this analysis: these reaches and steals are more of, uh, feelings. Like, it feels too late or it feels like a great price. I hope I can support some of these feelings with evidence. I typically hate relying on feelings, given I’m all about doing away with emotion, biases, and impaired thought processes to exploit market inefficiencies. But, hey. Let’s give this a shot.

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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 once made some bold predictions for 2016. Then I checked in on them. Some looked OK, some not so much.

The season is over now, and I can’t think of any better way to distract myself from the multiple painful ends to otherwise fantastic seasons I just endured than to review my bold predictions. Fellow RotoGrapher Justin Mason kindly said he “think[s I] nailed the boldness level. He also said, “Alex, you don’t know how [to] use [brackets].” Pffffft, whatever, Justin.

I would say I’m proud of these predictions, but honestly, I barely remember half of them. There are three I remember fondly, though, and I’m excited to see how they turned out. Let’s do this!

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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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It’s not as if the Chicago Cubs’ trade for started-turned-reliever-turned-starter Mike Montgomery came cheap. Dan Vogelbach isn’t a top-flight prospect, but with plus power and a solid plate approach at Triple-A Iowa this season, it’s not like he’s a nobody, either.

Then again, neither is Montgomery. A supplemental first-round pick almost 10 years ago, he was a Kansas City Royals top-5 prospect for four straight years and a Baseball America top-40 prospect for three of them. Then 2012 came; he was thrown into the James Shields–Wade Davis–Wil Myers–Jake Odorizzi blockbuster before continuing to generally fail to impress anyone. The Seattle Mariners acquired him in 2015, the year in which he debuted, in exchange for Erasmo Ramirez, and Montgomery delivered 16 suboptimal starts. He’s in Chicago now, providing relief every sixth day to a starting rotation that has generated the best staff WHIP in more than 100 years. Cool. Got that out of the way.

Montgomery is no ordinary sixth starter, though. I beg you to read this automated scouting report generated by Brooks Baseball regarding Montgomery’s pitches and their outcomes in 2016. Extreme number of ground balls. Blazing fast. Extremely high number of swings & misses. The remarks for all five of Montgomery’s pitches are, in a word, glowing.

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

* * *

It’s hard for me to feel like these rankings are worthwhile. Something like two-thirds of you are in your respective league’s playoffs or have already been eliminated. For those of you to whom this pertains, now we’re rolling the dice on small sample sizes — something inherently subject to volatility. Also, we’re practically a week into the month already.

So I won’t waste too much breath here. The following rankings reflect classic 5-by-5 rotisserie (“roto”) formats. Just please remember: this is your playoff hunt. If you play in a roto league, you know which categories you need to chase. I can’t answer that for you. But that category (or plural) are inherently more important to you, and you should value National League outfielders who contribute meaningfully to that category (or plural) accordingly. If you play in a points league, find power bats who minimize the split between their strikeouts and walks (assuming you are punished for the former and rewarded for the latter).

With that said, let’s dig in.

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