Archive for Starting Pitchers

wPDI & CSW: Whiffs

This is the second article of my series – wPDI vs. CSW. For those new to either metric, I will quickly catch you up. [The opening article can be found here.]

In last year’s FSWA Research Article of the Year, CSW Rate: An Intro to an Important New Metric, Alex Fast of PitcherList examines his site’s pitching statistic, CSW. The short and simple formula for CSW is defined as follows:

Called Strikes + Whiffs
Total Pitches

Independently, I came up with the concept of Weighted Plate Discipline Index (wPDI). With wPDI, we ask just three questions, or three binary events for every pitch:

  1. Was the ball thrown in the strike zone?
  2. Was the ball swung on?
  3. Did the batter make contact with the ball?

Every pitch can then be classified into 6 possible pitching outcomes based on the above. The definition of each outcome is as follows:

wPDI: Classifying the 6 Pitching Outcomes
Outcome Outcome Outcome Outcome Outcome Outcome
A B C D E F
Zone? Out of Zone Out of Zone Out of Zone In Zone In Zone In Zone
Swing? Swung On Swung On No Swing Swung On Swung On No Swing
Contact? No Contact Contact Made No Swing No Contact Contact Made No Swing

Each outcome is then assigned a weight, or an index. The formula for wPDI, the Weighted Plate Discipline Index is then given as:

wPDI = IndexA * A% + IndexB * B% + IndexC * C% + IndexD * D% + IndexE * E% + IndexF * F%

A% through F% are the percent of pitches thrown in each outcome, and the indexes are linear multipliers to obtain the aggregated, sortable metric.

What CSW has most in common with wPDI, is that it shares the same denominator – Total Pitches. That being the case, we can attempt to use the wPDI framework to express the PitcherList metric. CSW is rooted in Baseball Savant data, while wPDI is fed by FanGraphs figures. By exploring the similarities and differences between the metrics, we can also uncover some great nuggets of understanding.

Read the rest of this entry »


Pitch Mix Changes: Mengden, Velasquez, Cueto, & Wojciechowski

Again, I’m diving into some lowly-owned starters who have changed their pitch mix since last season. A couple seem to have potential.

Daniel Mengden (3% Owned at CBS)

Daniel Mengden’s Pitch Mix
Pitch Type 2019 2020 Diff
FA% 36% 54% 18%
SI% 17% 0% -17%
FC% 12% 2% -10%
SL% 14% 23% 9%
CU% 10% 10% 1%
CH% 11% 10% -1%
FS% 0% 0% 0%

While he’s better known for his 80-grade mustache, he’s trying to mix up his pitches to become useful. He’s reorganized a bunch of pitches that have helped but other parts of his game are dragging him down.
Read the rest of this entry »


Discussing the Pitcher Z-Contact% Laggards — 8/13/20

Yesterday, I identified and discussed the starting pitcher leaders in Z-Contact%, which is in-zone contact rate. Today, let’s look at the laggards in the metric. I’ll stick with the pitchers who have posted a rate of at least 90%.

Read the rest of this entry »


Discussing the Pitcher Z-Contact% Leaders – 8/12/20

It’s up for debate which one metric best describes a pitcher’s level of dominance. One of those metrics that doesn’t get as much press is Z-Contact%, which is defined as “percentage of times a batter makes contact with the ball when swinging at pitches thrown inside the strike zone”. In fewer words, it’s simply in-zone contact rate. Since all else being equal, a pitch thrown inside the strike zone is easier to make contact with then pitches thrown outside the zone, then one measure of absolute dominance is how often a pitcher generates a swing and miss on pitches thrown inside the zone. If a pitcher’s strikes can’t be hit, how are batters going to hit their balls (unintentional comedy scale: 10/10)?! So let’s look at and discuss the early starting pitcher Z-Contact% leaders. All these pitchers have posted marks below 80% versus a league average of 84.6%.

Read the rest of this entry »


Pitch Mix Changes: Duffy, Bundy, Gibson, & Fried

Hey everyone! Before we get started on pitch mix changes I figured I would introduce myself since this is my first article on Fangraphs. When I learned I would be writing for Fangraphs it felt like I had just won the lotto. As people would say these days, my mind was blown. For those who don’t know me, you can mainly see my work on my own blog and I am extremely active on twitter. I have an obsession with pitching, am a Mets fan (unfortunately), and my favorite pitcher in today’s game is, of course, Jacob deGrom. The baseball community is the best in the world and I couldn’t be more excited for this new adventure!

In this shortened season we sadly won’t be able to rely on a ton of metrics when analyzing pitchers. The sample size just won’t be big enough, but one factor that could be telling is pitch mix. We have seen numerous pitchers suddenly lean on different pitches, creating a significant difference in their performance (looking at you Patrick Corbin). Below are four pitchers who appear to be changing things up for the 2020 season. The question is, what does this mean for their future?

Danny Duffy

Danny Duffy
Pitch Type 2019 Usage 2020 Usage Difference
Fourseam 44.8% 40.5% -4.3%
Slider 26.4% 14.8% -11.6%
Changeup 11.6% 15.4% 3.8%
Curveball 9.0% 13.6% 4.6%
Sinker 8.2% 15.7% 7.5%

Danny Duffy came into 2020 with the mindset of keeping a pitch mix change he made towards the end of last season. In July and September (hurt in August) of 2019, Duffy started to get comfortable with his changeup. Most notably in September, he threw his changeup over 20% of the time, the first time he did that all season. In that month he threw for 30.1 innings while producing an impressive 2.37 ERA and 3.61 FIP.

Read the rest of this entry »


Randy Dobnak, Probable Great American Hero

It’s easy to dismiss Randy Dobnak, to turn him into a punchline. When 99.99% of baseball fans were introduced to Dobby last fall, they learned two things:

  1. When he wasn’t pitching, he worked part-time as a ride-share driver to help pay the bills (an altogether separate indictment of MLB and its broad moral shortcomings), and
  2. He has a handlebar mustache.

That’s just enough, but also plenty, to undercut a grown man’s legitimacy. It’s this very illegitimizing, I hypothesize, that has allowed Dobnak to fly under fantasy radars, even as he demonstrates nonzero aptitude on the mound.

Read the rest of this entry »


Pitch Mix Changes: Porcello, Gonzales, Lopez, Sheffield, & Freeland

I’m grinding away trying to find any pitchers who have changed their pitch mix and are flying under the radar. The changes could be for the better or worse. Also, I’m focusing on lowly owned guys. There is no reason to worry about pitchers who aren’t an option to cut or add. For example, Walker Beuhler has limited the usage of his four-seamer and curve and is throwing his cutter, sinker, and slider more. Sure he might change but is any owner going drop or bench him on the information.
Read the rest of this entry »


wPDI & CSW: Called Strikes

Introduction

Last year’s FSWA Research Article of the Year, CSW Rate: An Intro to an Important New Metric, was awarded to Alex Fast of PitcherList. In his article, Alex presents the pitching statistic, CSW – a metric which was originally coined and created by Nick Pollack in 2018. As cited in the author’s article summary, CSW is more predictive than Swinging Strike Rate (SwStr%), and is more descriptive than Whiff Rate (Whiff%).

The short and simple formula for CSW is defined as follows:

Called Strikes + Whiffs
Total Pitches

I enjoy elegant formulae. Sure – wOBA, wRC+ and the like are extraordinary metrics in their own right, but they are not the simplest to jot down. CSW is plain, simple, easy to understand, and nicely predictive.

Coincidentally, and unknowing of CSW, I came up with the concept of wPDI back in 2018. I then published my first works of the plate discipline framework on April 2, 2019. The original article was entitled Introducing: Weighted Plate Discipline Index (wPDI) for Pitchers, and can be found here.

What jumped out to me immediately upon reading Fasts’s article – was that the two metrics have something very in common. CSW and wPDI both share the very same denominator – Total Pitches. The base of both of our metrics are identical. Both utilize the very same sample size, both stabilize just as quickly, and both describe baseball through the very same lens – the pitch.

As a quick reminder of how wPDI works, every pitch can be classified into 6 possible pitching outcomes.

Read the rest of this entry »


Starting Pitcher Fastball Velocity Decliners – 7/30/20

On Tuesday, I shared and discussed the starting pitchers that have suffered the largest declines in their fastball velocity compared with 2019. A significant drop in fastball velocity could be a warning sign of injury, and already one decliner, Reynaldo Lopez, has hit the IL. Today, I’m going to update the list again with starters who have pitched since my last post. Once again, these are the starters whose “Pitch Type” fastball velocity has decreased by at least one mile per hour versus last year.

Read the rest of this entry »


Starting Pitcher Fastball Velocity Surgers – 7/29/20

On Monday, I shared and discussed the 10 starting pitchers that have increased their fastball velocity the most compared with 2019. Finding the early velocity surgers is one of the best ways to identify the season’s breakouts, as velocity has a high correlation with strikeout rate, so a higher velocity should result in more strikeouts, which should reduce ERA. Since it’s so important, I’m going to update the list again with starters who have pitched since then. Once again, these are the starters whose “Pitch Type” fastball velocity has increased at least one mile per hour versus last year.

Read the rest of this entry »