Archive for Starting Pitchers

2018 Mid-May Potential Starting Pitcher xwOBA Improvers

Earlier this week, I looked at Statcast’s expected metrics to identify hitters who may improve or decline from their current ISO marks. Today, let’s talk pitchers. I’m simply going to sort the Expected Stats leaderboard by difference between wOBA and xwOBA and discuss the fantasy relevant starting pitchers with the biggest negative gaps between wOBA and xwOBA (higher wOBA than xwOBA). Remember that xwOBA fails to account for home ballpark, defensive support, quality and opposition, and perhaps other factors I’m not able to come up with at the moment. It’s why I stick to the extremes, as even with all factors accounted for, it’s highly likely these guys are still due for the same directional move in wOBA, though perhaps not to the same degree.

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The Slate – May 16th, 2018

Note: This post was scheduled for the early morning, but didn’t go through. If I do this again it the future, it will post in the morning. 

A look at the most interesting pitching performances from last night and what I’m looking forward to on Wednesday’s slate.

About Last Night

Some quick thoughts on the most interesting starts of yesterday:

Jordan Lyles (7.3 IP/0 ER) was perfect for 22 outs before a Trevor Story base hit. A walk to Pat Valaika immediately after ended his excellent day. It was Lyles’ second strong start since joining the rotation, but his big outing further underscores the issues against righties for the Rockies offense. Their 64 wRC+ versus righties is dead last in the league and their 25% strikeout rate is fifth highest. As for Lyles, he is throwing 94 mph (a career-high) and his curveball is working as well as ever. He was second to only Thor with 16 swinging strikes on Tuesday. He’s got the Dodgers and Nationals both on the road in a two-start setup next week. Let’s give him a shot.

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Freddy Peralta’s Fastball(s)

In my last article, I did a Quick Look at Freddy Peralta and found his fastball fascinating. He manipulated the pitch to provide the look of different pitches by changing his grip. What I wanted to know is if he could get by with just a good, varying fastball.

First, everyone needs to take a trip over to Peralta’s game page at BrooksBaseball.net and examine the pitch groupings. Usually, different pitches form clusters when examining variations in break, velocity, and spin. Ignoring the possible changeup, he has two groups, fastball and curve. His fastball has an estimated spin which varies from 1300 rpm to 2500 rpm. Its velocity differs from 88 mph to 97 mph. The spin values on Brooks are interpreted based on the ball’s break. The spin rates may be off because Peralta releases really close to home as Jeff Sullivan documented.

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Quick Looks: German & Peralta

Freddy Peralta

• I got swamped last night during my chat on Peralta questions. I just didn’t know much about him so I went and watched his debut.

• It looks weird in that he is nearly falling down on every pitch and just averaging 90 mph on his fastball. It reminds me of high pitchers trying to reach 85-mph.

• Fastball: It sat at 87-95 mph with some nasty glove-side run. It could be considered a cutter at times. He used it like Mariano Rivera did by changing the spin. Partway through the game, MLB Gameday started labeling some of his pitches as cutters. It was not two separate pitches since there was no unique spin-velocity grouping

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Addition by Subtraction: Fixing Dylan Bundy Long-Term

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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Is There Any Hope For These Disappointing Starting Pitchers?

For the vast majority of the season, I completely ignore ERA, instead relying on SIERA for rest of season projection purposes. While this method is far better than looking solely at ERA, what about the pitchers you expected to be good, but have been terrible, with weak skills to match? These are the guys whose SIERA confirms they have pitched poorly, but that doesn’t necessarily mean they will continue posting such weak skills. So let’s discuss three starters we expected better from, but whose current skills don’t provide much hope for a rebound.

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Sporer Report Issue #6 – Romero’s Rising

If you scooped Fernando Romero off your waiver wire on Sunday night, you were paid immediate dividends as the 23-year old righty threw six scoreless innings in St. Louis on Monday night, allowing just three hits and three walks while striking out nine. He now has 11.7 scoreless innings to open his MLB career and has many wondering if he can be a game-changing rookie for both the Twins and your fantasy team. He has consistently been a Top 10 entrant in Twins prospect lists for the last couple years including 7th by Eric last year and will place top five for this year’s list, which is coming soon. Let’s take a closer look at the electric righty.

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Jose Berrios Is Bucking the Wildness Trend

Strikeouts are up again this season, but there’s another trend affecting pitchers that has received less attention. As we approach the six-week mark of the 2018 campaign, pitchers are notably wilder than they have been in a long time.

For each season between 2011 and 2016, the average Zone% for the major leagues hovered between 44.2 and 44,8 percent. Last season, pitchers were less wild than they had been since 2010, locating in the strike zone at a 45.0 percent rate. So far this year, pitchers are wanting to have much less to do with the strike zone, as their collective Zone% has dropped to 43.4 percent.

Subpar control is not an early-season thing. Last March and April, pitchers combined for a 44.8 percent Zone% and in the previous March/April, pitchers were practically trolling hitters into swinging, posting a 47.3 percent Zone%. Another thing that mark from 2016 shows is that there is still plenty of time for Zone% to regress to its norm this season.
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ERA Minus SIERA Laggards: Gonzales, Archer, Gray

FanGraphs hosts a statistic for pitchers called ERA Minus FIP (“E-F”), which is as advertised. FIP being a (somewhat) adequate measure of pitcher over-/under-performance, one could look to E-F to identify pitchers who may, as they say, be due for regression. FIP’s correlation with ERA, however, is weaker than that of xFIP due to the former’s inability to account for the volatility inherent to home run-to-fly ball ratios (HR/FBs). To take it a step further, xFIP’s correlation with ERA is weaker than that of SIERA due to the former’s inability to account for a pitcher’s ground ball rate (GB%) and how it interacts with his strikeout and walk rates (K%, BB%).

Alas, I often use SIERA, rather than xFIP or FIP, to identify pitchers who may be ripe for regression. ERA Minus SIERA (“E-S,” henceforth) is not the be-all, end-all by any means, and I would never consider making a roster decision based exclusively on that metric. Player evaluation is a holistic endeavor, which you likely know yet I still intend to demonstrate. Three names stood out to me — four, if you include Luis Castillo, but I covered him a week and a half ago — as interesting E-S targets, but I came away from this feeling good about only one of them.

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May Starting Pitcher Rankings Update

Wow, I can’t believe we’re already a month into the season! A quick refresher on how I put these together. This is a narrower focus than just “rest of season” as I’ll be updating these every month. Pitching is just too volatile to have confidence in a single ranking set for more than 4-6 weeks at a time. The tiers are more important than the numerical ranking as they’ll guide the start/sit decisions more accurately.

I want to be clear that the Must-Starts aren’t automatically the best pitchers, but rather the guys that you can’t sit with any confidence. Do I really think that (spoiler alert!) Sean Manaea is the 27th-best starter for the rest of the season? I have hard time saying that, but there is no circumstance where I’d bench him right now.

Please leave your questions and comments below!

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