Archive for starter

I’ve had the question written on my whiteboard for ever: are foul balls good or bad? It’s a glass-half-empty, glass-half-full conundrum. The former group might think a foul ball is simply a barely-missed opportunity at in-play contact. The latter group might view that same event as a positive — that the poor quality of contact on a foul ball is indicative of an ability to induce poor contact quality in general, and it’s not inherently different from a swinging strike.

In my heart of hearts, it makes more sense to me that a foul ball is closer to in-play contact than not. Considering the diameter of both a bat and a ball, and the nearly physically impossible feat of connecting the two in motion, a foul tip has a margin of error of mere inches, whereas a swinging strike, fully sans contact, can have a margin of error measured in feet. Yes, it seems like getting a piece of the ball suggests, from the pitcher standpoint, makes the glass appear more half-empty than otherwise.

I wanted to finally tackle the subject, but I didn’t really know how. I first looked at the outcome of the pitch directly following foul and non-foul pitches, but it was a bit noisy (although, to be fair, I may have missed clear patterns in that noise). I imagine the effects spawning from a foul ball are not exclusive to the next pitch; rather, they may manifest two or three or even four pitches deeper into the plate appearance. In other words, a pitch-sequencing analysis might be prohibitively difficult, at least for someone like me who lacks the brainpower or mental stamina to pull it off.

Instead, I opted for something a little easier yet arguably just as telling. Read the rest of this entry »

Last week, I recommended an improvement for expected fielding independent pitching (xFIP) without dismantling the original FIP framework upon which it was built. FIP describes the relationship between ERA and strikeouts, walks, and home runs allowed; xFIP does the same but attempts to remove the luck component from home runs by multiplying the number of fly balls a pitcher allows by the league-average rate of home runs to fly balls (HR/FB) — the rationale being HR/FB is notoriously fickle to project year to year.

The recommendation: change HR/FB to include line drives (LDs) and exclude infield fly balls (IFFBs, aka pop-ups). It’s worth noting our dark overlord David Appelman once explained how removing pop-ups from aggregate fly balls insignificantly affects xFIP. Additionally, less than 1% of line drives result in home runs. The recommendation, then, seems like the merging of two separate but equally fruitless endeavors, given the facts.

Yet changing the HR/FB component in xFIP to be “HR/(oFB + LD)” substantially improved the metric’s correlation with same-year ERA. Adjusted r², which measure the strength of relationship from 0 to 1, increased from 0.42 to 0.55 using Statcast data (0.44 to 0.53 using FanGraphs data). I hypothesize that, when added to fly balls, line drives (despite resulting in very few home runs) give a more holistic indication of the average contact quality and launch angle a pitcher allows.

Today’s recommendation: account for start/relief splits.

Although I thought of this independently, the idea itself is far from an original one. Read the rest of this entry »

(Not to be confused with Jeff Zimmerman’s delightful Quick Looks.)

In terms of fantasy topics to discuss, I’ve been pretty unmotivated for the last month. I took to Twitter to solicit some ideas. Rather than letting myself procrastinate and become unmotivated about these interesting topics, I figured I’d knock a few out at once with some quick takes.

The re-emergence of Ben Zobrist

Or, conversely, the caving-in of the rest of the Cubs’ offense.

Sure, there have been bright spots: Javier Baez makes for a nice down-ballot MVP candidate, Kyle Schwarber is not a liability, and Jason Heyward is a non-zero with the bat for the first time since moving to Chicago. But for everyone else? Not so much.

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If something about Madison Bumgarner’s first eight starts of 2018 have seemed odd to you, it’s because they have been. No matter the fielding independent pitching statistic to which you subscribe — FIP, xFIP, SIERA (although, frankly, it should be SIERA) — Bumgarner’s 2018 has not inspired confidence. Despite a dazzling (and quintessentially Bumgarnerian) 2.90 ERA, his baserunner suppression skills (i.e. strikeouts and walks) have lagged this year, and the various FIPs all portend severe bumps in the road. Granted, Bumgarner has outperformed his FIPs the last three years and throughout his career. I’m here to argue not that we should dismiss our concerns because of this but, instead, that such overperformance has insulated us from what should be potentially serious concerns about MadBum’s long-term health and success.

The problems with Bumgarner’s 2018 season — or at least the peripherals that underpin his 2018 season — thus far stem back not to his broken finger but, rather, something both farther back and much more dire. You may or may not recall Bumgarner fell off a dirt bike last year and injured his throwing shoulder. He returned from that injury almost exactly a year ago and promptly underwhelmed us. Sure, he posted a 3.43 ERA through September and has a 3.23 ERA in the calendar year since his return. It’s not vintage Bumgarner, but it’s not awful. But the peripherals, oh, the peripherals: his strikeout rate (K%) has caved dramatically, falling more than 6 percentage points (27.1% from April 2015 through April 2017; 20.9% from July 2017 onward).

It’s his fastball. Bumgarner’s fastball, once elite (relative to other four-seamers), is broken, and it has been broken for a year.

Read the rest of this entry »

Some good pitchers, despite being good pitchers, throw bad pitches. And there are bad pitchers, too, who throw good pitches. Both are true, and one could make an argument a Venn Diagram of the two groups may overlap significantly, and that overlapping area is the group of pitchers toeing the line between breaking out and being unusable for fantasy purposes.

It stands to reason, then, that good and bad pitchers could benefit from easing off or completely abandoning their bad pitches. It’s one thing to evaluate a pitch based on its underlying metrics — its swinging strike rate (SwStr%), its ground ball rate (GB%), its velocity, and so on. It’s another thing to evaluate the pitch objectively by looking at its weighted on-base average (wOBA) allowed, which, I hope, in an adequately large sample, can indicate a pitch’s quality regardless of its peripherals. In theory, the larger the sample size, the greater the probability a pitch’s outcomes will converge with its inputs, such that the caveat “regardless of its peripherals” doesn’t actually mean anything. Given enough pitches thrown, the aforementioned underlying metrics will adequately inform the wOBA allowed.

Using PITCHf/x data from the last two years, I looked for (1) good pitchers who throws pitches that allow (2a) extremely bad wOBAs with (2b) unusually low BABIPs. Incurring high wOBAs on low BABIPs is less than ideal; if BABIP is subject to high variance and generally converges on the league average, then a bad pitch being “lucky” by BABIP suggests things will only get worse.

This post was going to be about several pitchers, each with their own problematic pitches, but I became too passionate about this single case. This is about Dylan Bundy, his abhorrently bad four-seamer, his fantastic slider, and how much his pitch selection is suffocating his potential. Ultimately, it’s about adding by subtracting.

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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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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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Yesterday, Mike Podhorzer gave you 10 pitchers to start for yesterday (and yesterday only). Indeed, the well of relevant advice has run dry save a few drops here and there, yet it’s too early to look forward to offseason chatter.

You all liked Pod’s idea, though; you just needed the advice in advance. Still, continuing this pattern leaves us without any names for today. Perhaps you’re in a league where you can make moves prior to the day’s first game. If that’s the case, then I hope this helps! You have about 45 minutes until day games start.

Games are ordered by start time per ESPN. And, for your convenience, here’s some color-coded goodness: No-Brainer, Maybe, Sit (or a desperate deep-league play)

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