Archive for Starting Pitchers

Even though we are about halfway through the season, the league leader in innings pitched sits at just 40.2 innings. That’s far too small a sample size to find much meaning in traditional surface statistics such as ERA and WHIP (plus LD%, HR/FB, BABIP, etc). The results that feed into ERA take significantly longer to stabilize, so it makes more sense to focus on the underlying skills that pitchers have more control over. Luckily, we have a metric that takes all those underlying skills, throws them into a blender, and spits out a skills-based ERA. Of course, I’m describing SIERA, and it’s what I exclusively look at early in the season to forecast future performance, as it’s far better than ERA itself. So with that said, let’s take a gander at the top 20 qualified starting pitchers in SIERA and discuss any surprises.

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SwStr% is a simple metric that is calculated by taking swings and misses and dividing it by total pitches. Why is SwStr% important? Simply put, if a pitcher can produce a bunch of swings and misses it means his strikeout rate should be high. The more strikeouts the better, because if you look at an elite pitcher in baseball you will see a high strikeout rate. It is well known that SwStr% correlates well with a pitchers strikeout rate. Want to know if a player’s K% is over or underperforming? Check out their SwStr%. The rule of thumb (although it isn’t exact) is to double a pitchers SwStr% and their K% should be around that number. Keep in mind some pitchers will be outliers if they consistently rely on called strikes, like Aaron Nola.

Let’s take a look at the SwStr% leaders so far this season.
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With a mid-to-high 90s fastball that has touched as high as 101 MPH and an elite splitter that has generated a SwStk% over 20% every season of his career, a lot has been expected of Kevin Gausman. You figured that with a two-pitch foundation like that, he would be racking up the strikeouts and rank as one of the better pitchers in baseball on an annual basis. And while he’s posted a couple of seasons of sub-4.00 ERAs, the underlying skills just haven’t been super impressive, and he sports a career ERA of 4.31. That’s perfectly serviceable, especially in a hitter friendly home park for most of his career in the American League. Sure enough, his career ERA- stands at an almost perfectly league average 101. So he’s been fine, but not what fantasy owners hoped for.

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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:

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

wPDI = Index_A * A% + Index_B * B% + Index_C * C% + Index_D * D% + Index_E * E% + Index_F * 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.

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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)

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.
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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%.

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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%.

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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 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.

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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.

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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.
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