Archive for 2017

As a Twitter dork, I’m exposed to a lot of discussion about swinging strike rates (SwStr%), so much so that it almost feels like it has supplanted xFIP (or other comparable metrics) as a catch-all way to evaluate pitchers. Dude has a 12.5% whiff rate! Sweet. It’s not for naught — swinging strike rate bears a strong correlation to strikeout rate (K%), which comprises substantial portions of the regression equations that underpin the aforementioned xFIP and its counterparts. Swinging strike rate’s correlation to the following metrics (using data from the last five years of 714 pitchers who threw at least 100 innings in a given season):

• K%: r = 0.83
• SIERA*: r = 0.61
• xFIP*: r = 0.55
• FIP: r = 0.50
• ERA: r = 0.40

(*See footnote.)

It also correlates strongly year over year (among 392 player-seasons during the same timeframe in which the pitcher threw 100 innings in the current and subsequent seasons):

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And it’s evident you should now pay attention to him. Jeff Sullivan wrote about Miles Mikolas here — Sullivan does a good job of summarizing Mikolas’ skill set and how he’ll succeed stateside. Which is helpful. But, for fantasy purposes, it doesn’t help us a whole lot in terms of exactly what we should expect. Not that that’s Sullivan’s fault. He doesn’t keep a cross-league projection system in his brain.

So when you see a Tweet like this — from NEIFI Analytics, which FanGraphs has featured previously — it’s hard to ignore:

Congrats, Cardinals. Per NEIFI, Mikolas handily outperforms Jake Arrieta over next three seasons. Massive bargain, fantastic bet to be the most underrated FA of 2017 class.

— NEIFI Analytics (@NEIFIco) December 5, 2017

Then again, there are Tweets like this from ZiPS’ own Dan Szymborski:

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This review was written with permission — I asked, not the other way around — and was not reviewed prior to publication.

There exists several gatherings for baseball enthusiasts every year, including, off the top of my head, MIT Sloan Sports Analytics Conference, SABR Analytics Conference, Saber Seminar and Pitch Talks. However, I can’t name many, if any, conferences that cater specifically to fantasy baseball enthusiasts other than First Pitch Arizona (FPAZ). It’s not that the other conferences wouldn’t benefit fantasy baseball players — surely, they share sharp, illuminating content — but they don’t synthesize it specifically for the fantasy baseball experience.

Brent Hershey, general manager of BaseballHQ, invited me to speak on a panel with Greg Ambrosius (National Fantasy Baseball Championship, or NFBC), Dave Potts (RotoGrinders) and Brian Slack (BaseballHQ) about 2017 average draft position (ADP) musings. For an event in its 23rd year, I could find scarcely any reviews of the conference aside from these testimonials.

Accordingly, I thought it would be worthwhile to allow readers to learn (more) about the event. I’ll provide a brief overview of everything and then break down the programming by day, almost like I’m writing in my diary, except without the anxiety and self-doubt.

Overview

FPAZ occurs every year the weekend of the Arizona Fall League (AFL) Fall Stars Game (typically the first weekend of November) in Phoenix, Ariz. Registration costs $249 for early birds and $499 for late birds. The conference spans four days, four nights — for this year, the evening of Thursday, Nov. 2 through the morning of Sunday, Nov. 5 — and includes two tickets (or more, depending on availability) to any AFL games playing that weekend and, once available, all of BaseballHQ’s major publications. It also provides breakfast each morning and a buffet lunch on Saturday on site. Exact programming is liable to change from year to year, but a couple of panels (based on cornerstone BaseballHQ content) likely stay the same. Hotel fare is not covered, but the conference took place at the DoubleTree suites by Hilton, which is where most attendees stayed.

Thursday

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In the two previous years I’ve curated the RotoGraphs staff picks, I evaluated them during the post-/offseason to determine which staff writer had the best time pickin’. What good are our allegedly “expert” picks if we don’t hold ourselves accountable?

You can find this year’s preseason picks here. The best pick in each category is an indiscernible blend of talent (duh) and uniqueness (like, Andrew Benintendi as a Rookie of the Year candidate is not very original, so I’d dock you points for that). Most correct (with air quotes) picks wins. Let’s go!

(Shallow) Sleeper (ADP 201-300, per NFBC ADP)

Pitcher: Robbie Ray (Brice Russ, Jeff Zimmerman)
Hitter: Domingo Santana (Al Melchior, Birchwood Bros., Justin Vibber)

There are three standout picks here, but one stands above the rest. I have written repeatedly (aka twice) about Ray’s rollercoaster career and baffling peripherals. He has delivered consecutive seasons of extreme outliers; his true self is probably a perfect blend of 2016 and 2017, which is roughly a mid-3.00s ERA with league-leading strikeouts and potentially league-trailing walks (and, also, league-trailing contact management). He is Yu Darvish’s stateside-produced clone, and early evidence (#2early mock drafts, henceforth) suggests he’ll be drafted as such.

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I talked a big game about my bold predictions this year spawning from research. Like, instead of just being gut instinct types of things, or just being bold for the sake of being bold. Truth of it is I didn’t do as much research as I would’ve liked. My rotisserie-league drafts were not particularly strong, and while I hit the trifecta (1st, 2nd, 3rd) in my three home leagues (I live modestly), I could simply feel my drafts, as well as my bold predictions, were inferior relative to what I hoped they’d be.

You probably don’t care, though, so this is all filler text, for all intents and purposes. You want to cut to the chase. I don’t blame you! Let me drag this out a bit longer. I’ll review each prediction from March with their corresponding midseason “probabilities” of being correct from July before finally reaching a verdict. I don’t remember half the predictions and I honestly have no idea how I’ll do until I reach the end.

1) Alex Dickerson is a top-30 outfielder. (Midseason odds: 0%)

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This is a long one. I appreciate your patience in advance.

Mike Podhorzer, I and sporadic others have — but primarily Mike has — carried the torch on developing ‘expected’ metrics, such as xBABIP (expected batting average on balls in play), xHR/FB (expected home run-to-fly ball ratio) and xK% (expected strikeout rate), all and the rest of which can be found here. For the uninitiated, these xMetrics help describe how a hitter or pitcher should have performed based on various measurements of the events that unfolded and typically are more predictive of future performance than the original metric. They’re not perfect, but, like other advanced metrics, they give us a better understanding of player performance and ability.

Each metric — xHR/FB, xK%, etc. — has formulas for both hitters and pitchers, with the hitter metrics typically having stronger correlations than those for pitchers. Unfortunately, pitcher xBABIP has always eluded us. It’s inappropriate to repurpose hitter xBABIP for pitchers, but it’s because the model coefficients (weights) would be different, not because the theory underpinning the model is flawed.

That’s the problem, though: hard hits, line drives, infield fly balls — these all should affect a pitcher’s BABIP allowed. Our intuition begs it to be true. Yet there’s a resounding lack of evidence that suggest otherwise. The correlation between BABIP and hard-hit rate (Hard%), line drive rate (LD%) and infield fly ball rate (IFFB%), among others, borders on nonexistent:

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Bold predictions are inherently jovial, whimsical, outlandish, possibly even blasphemous. You know you probably weren’t bold enough if you got too many correct, and you probably were too bold if you got too many incorrect. Mine typically follow suit. I don’t expect to get every prediction correct by the numbers, but I do hope each prediction is correct in spirit. My “spiritual” success in this regard, I’ve noticed, typically reflects upon how well my teams performed in a given season. Accordingly, I take my predictions seriously, and I sincerely use them as a collective barometer for how I had gauged value plays in the preseason.

I don’t remember any of my predictions, really, and I’m revisiting them in real time with you. My teams are doing well this year — 1st, 2nd, and 3rd in my three home leagues (humblebrag) (no expert or high-stakes leagues this year) — but I have a feeling my predictions have not stood the test of time. Again, this is to be expected. But, again-again, I’m not sure they’ve held up spiritually, either.

Here goes:

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You know the drill! The criteria for each “award,” so to speak, precede each table. Pitchers first, then hitters. Here are last year’s picks, by the way.

* * *

Pitchers

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My first attempt at making bold predictions (2015) was rather aimless. My second attempt (2016) was a little more focused and a little more successful, with my baby boo Jose Ramirez finally making good on his promise (and redeeming my year-too-early prediction for him in 2015). This year, I’ve earnestly attempted to make bold predictions that spawned from research. In other words, they’re not bold for the sake of being bold — not that those kinds of predictions can’t be fueled by research, but, well, you know. Anyway, you don’t care about any of this. Let’s get to the goods.

For those keeping score at home: five predictions apiece for hitters and pitchers, in alternating order.

1) Alex Dickerson is a top-30 outfielder.

Original post from September. The premise is simple: keep an outfield job and sustain his place discipline gains. With prospects Hunter Renfroe and Manuel Margot and speedster Travis Jankowski fighting for playing time, Dickerson seems to have fallen to the wayside. I’m not sure why; he projects to be the Padres’ 4th-best hitter by wOBA and best-hitting outfielder by more than 30 points. Accordingly, the projection systems must believe in his plate discipline gains — and they do. The doubters will doubt, but the gains emerged in 2016 prior to his promotion. In a full season’s work, he looks like a poor man’s outfielding Kyle Seager: 20 home runs, 10 steals, a .270 batting average. As the 70th outfielder off National Fantasy Baseball Championship (NFBC) draft boards, it’ll cost you virtually nothing to find out.

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No need to fret. The unofficial conductor, who is also the author of this post, does not expect the cabin to reach capacity. Not prior to April, at least.

Brett Lawrie’s time with any organization, not just the White Sox, was ticking away; more writing was scribbled on more walls with each passing year since his debut. So when the White Sox released Lawrie, the first thought on most fantasy owners’ minds was not Where will Lawrie end up? but, rather, When will Yoan Moncada get the call? Moncada, a consensus top-5 prospect, changed socks and is now the marquee name of the South Side’s now-promising future.

Yet one could argue Moncada’s not quite ready for the big show. After raking and running absolutely wild in High-A in 2016, Moncada graduated to Double-A and, well, his performance is open to interpretation. On one hand, his 11 home runs, nine stolen bases and .277/.379/.531 triple-slash in 207 plate appearances amounted to a batting line that was more than 50% better than the league. On the other hand, he struck out more than 30% of the time — and that lack of contact carried over into his Major League debut, during which he struck out in 12 of 20 PAs. The tools are immense, but, at 21, he could definitely use some polish, and the White Sox have no incentive to rush him along.

Allow me to (re)introduce you to Tyler Saladino.

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