Archive for SP

Masahiro Tanaka and Jeff Samardzija had perplexing, enigmatic, and ultimately bad seasons. Many attempts were made to ascribe reasons or causes for their struggles. I think both will bounce back for very simple reasons; accordingly, I think both will be undervalued in 2018 for equally simple reasons.

Masahiro Tanaka

Travis Sawchik and Eno Sarris discussed his various ailments, so to speak, long after I gave up trying to diagnose him. The heat maps are interesting, and the splits are interesting, albeit a bit of an archaism.

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I’m already thinking about 2018. It’s not that my teams are doing poorly; they’re fine, for the most part. It’s that the economist nerd in me, when thinking abut fantasy baseball, most often evaluates the disparities between perceived and actual values, and how long, if ever, it takes for the market (aka fantasy owners) to come to equilibrium, to use economic parlance.

For example: you may or may not be aware that Kevin Gausman, despite his atrocious start to the season, has been magnificent the last five weeks. In seven starts from July 2 onward, he’s posted a 3.24 ERA (supported peripherally by a 2.81 xFIP and 3.40 FIP) with 11.4 strikeouts and 2.6 walks per nine innings. The strikeout rate is fueled by a 15% swinging strike rate (SwStr%), which have come consistently, ascending into double-digit percentages in all seven starts (and in eight of his last nine). His strikeout-to-walk differential (K-BB%) by month: 2.0%, 8.8%, 9.2%, 23.4%, and, in one August start, 28.0%.

Meanwhile, he’s inducing ground balls almost half the time (49.5% GB). You could say he’s due for batting average on balls in play (BABIP) regression, and he probably still is. His BABIP constantly hovering above .349 does not inspire confidence, but few pitchers have ever been BABIP’d so hard in a single season — I discussed this phenomenon in regard to Robbie Ray. All said, while there’s no guarantee his BABIP regresses before October, Gausman still shows the promise we once expected of him — perhaps more — and it’s going largely unnoticed because of his downright repulsive first half. (He’s baseball’s #12 starter the last month.)

Such is the gist of this post, in which I’ll briefly touch upon players I anticipate to have average draft positions (ADPs) in 2018 that will lend themselves to relatively low-risk, high-reward opportunities in standard mixed leagues. Whether such expectations become reality is another story; that’s why I’m relying on ownership levels as a proxy for perceived value. All ownership levels likely retain some amount of draft day inertia, for better or for worse — in other words, leftover ownership (or lack thereof) in abandoned leagues — so take it all with a grain of salt.

Please note this is, by no means, an exhaustive list — just the first few players who come to mind, mostly because I’ve paid close attention to them all season.

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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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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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Funny how we have not written much at FanGraphs about Robbie Ray this season. Eno Sarris lauded Ray’s velocity in brief in the spring; in July I expressed enthusiasm in Ray but didn’t give him the most glowing recommendation; all of which finally culminated with August Fagerstrom’s piece two-and-a-half weeks ago declaring Ray MLB’s newest strikeout madman. That actually seems like a lot of coverage, now that I mention it all, and it kind of is. But it’s all more recent and probably deserved to happen sooner, especially since Ray has posted a strikeout rate of 9.6 K/9 or better in every month this season.

Sarris noted that Ray is mostly a two-pitch guy, thereby dampening his value. Fagerstrom uncovered related weaknesses during Ray’s third trip through the order, likely correlating negatively with his lack of variety. Then again, Fagerstrom acknowledges how big a role sequencing plays in a pitcher’s success, and Ray has been woefully unlucky in this regard, forcing the split between his ERA and FIP (E-F) wide open.

Let’s play pretend. Let’s say Ray never develops a third pitch. Let’s say Ray rides the status quo through next season. Would that be so bad? Probably not, because Ray is doing his best Yu Darvish impression (sound familiar?):

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A pitcher’s excellent performance early in the season can obscure poor performance later on, as his stats slowly converge toward expectations. If you held onto Jordan Zimmermann too long, you suffered the consequences. The same applies for the opposite scenario; Matt Shoemaker has been one of the baseball’s better pitchers since mid-May after an atrocious start to the season.

Alas, the deeper we get into the season, the more important it becomes to check recent leaderboards. With the way player performance ebbs and flows during a season, a span of five or six starts can probably be considered a small sample size. Still, keeping an eye on these small samples can illuminate interesting trends.

For whatever reason, there seem to be a lot of unfamiliar or unexpected names on FanGraphs’ xFIP leaderboards under the “last 30 days” split. Let’s break them down!

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Never before have we seen so many talented young pitchers. And, although I don’t have concrete evidence to support it, it feels like we have never seen so many name-brand starting pitchers struggle.

Everyone slumps. David Price, for example, is slumping. But with an atrocious strand rate (LOB%) and elevated batting average on balls in play (BABIP), it’s the type of slow start that savvy fantasy owners should target as a buy-low opportunity.

Other starters enduring equally slow starts can’t be defended quite as easily. Inversely, still more starters are masking their ugly peripherals with typical production, as expected. You may want to consider selling the names below. All three make me sad because, while not especially old, each of them has stared down his mortality at one point or another this season, as we normal folk do every day when we look in the mirror. All our demises are imminent, a truth made painfully true by the beautiful yet cruel sport we love so.

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This kind of post is right in Mike Podhorzer’s wheelhouse. We have a lot of common interests as far as baseball research topics are concerned — namely, xK%, xBB% and xBABIP — but he’s typically the one who periodically updates RotoGraphs with x-leaders and x-laggards.

So, again, this would be the kind of post Pod would tackle: an update on which starting pitchers will likely regress in their strikeout rates (xK%). But instead of using the xK% equation, to which the above paragraph is hyperlinked, I want to focus on a particular metric: zone contact rate, or Z-Contact%.

I’ll be up front about this: I haven’t done much research regarding pitcher zone contact rates and how it sticks from year to year. That’s primarily what this post will entail, and my evidence is largely anecdotal. But it’s important to note that zone contact rate plays a profound role in determining a pitcher’s strikeout rate; the Pearson correlation coefficient between K% and Z-Contact% is -0.72. In other words, K% and Z-Contact% are strongly negatively correlated.

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The best of, worst of awards continue this week along with a spotlight on fantasy baseball’s catcher landscape in 2015. Last week, I awarded the 2015 Sigh Young — fantasy baseball’s biggest pitching bust — to Jeff Samardzija, who miserably underperformed expectations en route to a pretty awful season.

The 2015 Roto Overhyped Pitcher award is a bit different and probably more subjective. Rather than simply be bad, a pitcher must have also been over-hyped. Too much hype typically occurs for two reasons, neither of which are mutually exclusive:

1. The pitcher was once a top prospect
2. The pitcher broke out, or turned the corner, the previous season

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