As we enter the final full week of the season, streaming starting pitchers to try to maximize your wins and strikeouts might either become a viable strategy for you now or has been a strategy you have been executing for some time already. So let’s review the probable starters for Tuesday’s games that are owned on 30% or fewer teams in CBS leagues and conclude with a STREAM or NOT decision, assuming a 12-team mixed league.
This is the fourth article in my wPDI vs. CSW series. You can catch up by reading the first three articles – on called strikes, whiffs and residuals.
Here is a quick summary of some of the basics of wPDI & CSW from this series:
Last year, I developed the Weighted Plate Discipline Index (wPDI) framework, whereby all pitches can be classified into six different outcomes as follows:
| 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. A% through F% are the percent of pitches thrown in each outcome. The general formula for wPDI, the Weighted Plate Discipline Index is given as:
wPDI = IndexA * A% + IndexB * B% + IndexC * C% + IndexD * D% + IndexE * E% + IndexF * F%
wPDI can generate an all-in-one sortable metric used to evaluate pitchers. The plate discipline framework may be tailored to mimic (or to correlate to) various measures of deception or effectiveness.
In the first three articles of this series, we developed indices for wPDI to approximate the PitcherList metric, CSW. The Called Strikes + Whiffs (CSW) statistic was featured in last year’s FSWA Research Article of the Year by Alex Fast, and is defined as:
Called Strikes + Whiffs
Total Pitches
We separately tacked the called strikes and whiffs components, and landed on the following wPDI equation to represent CSW: Read the rest of this entry »
This season, this short, crazy, and insane season has seen a lot of rookie pitchers. With all of the call ups, this has been one of the more compelling MLB seasons we have seen in a long time. It seems like every week there are new pitchers being called up to grab a spot start. Pitchers who haven’t even reached the AAA level. Most importantly pitchers that we have been waiting a long time to see. There will be two parts to this article as we will analyze some of these rookie pitchers, how they are performing, and what their future holds.
09/10/20
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The 2021 draft season will be interesting, to say the least. There has been an abundance of surprises when it comes to starting pitchers. For instance, Zach Davies, Corbin Burnes, Dallas Keuchel, Framber Valdez, and Adam Wainwright all have a sub-three ERA. What’s going to be strenuous for 2021 is figuring out who is “real” and who isn’t. How do we do that? Well, there are several factors such as a pitch mix change, movement changes on pitches, and velocity. With all that said there’s (at least) one pitcher performing well who seems to be legit. That pitcher is Pablo Lopez.
This is the third article in my series – wPDI & CSW. You can catch up by reading the first two articles – on called strikes and whiffs – found here and here.
Here is a quick recap of what we have covered so far:
In this series, we are looking at the PitcherList metric, CSW and how it relates to my plate discipline framework, wPDI. Last year’s FSWA Research Article of the Year by Alex Fast featured CSW, which is defined as:
Called Strikes + Whiffs
Total Pitches
With the Weighted Plate Discipline Index (wPDI) framework, all pitches are classified into six different outcomes as follows:
| 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. A% through F% are the percent of pitches thrown in each outcome. The general formula for wPDI, the Weighted Plate Discipline Index is given as:
wPDI = IndexA * A% + IndexB * B% + IndexC * C% + IndexD * D% + IndexE * E% + IndexF * F%
The Padres are trying to set the trade deadline record for most players traded and have acquired perhaps the most valuable one available in Mike Clevinger. In the past, like as recent as last season, a move for a starting pitcher to the National League would be a boon, as he would no longer have to face the DH most of the time, except for when playing an interleague game in an AL park. The introduction of the universal DH this year removes that performance boost, so now we can easily compare apples to apples. So let’s take a look at the 2019 park factors and compare the Indians and Padres home parks to find out if Clevinger’s value changes at all solely based on his new home park.
For those who don’t know, I started in this industry with a focus on streaming pitchers. By using various statistics for both pitchers and their opponents I have been providing advice to followers on who to stream in their leagues. What does streaming pitchers mean? Simply put it means grabbing a pitcher off your waiver wire for one start. You choose that pitcher based on matchup and skill hoping they provide you with decent ratios and then dump them back into the free-agent pool.
With that said it is important to know which pitchers are worth streaming in certain matchups. These pitchers typically aren’t good enough to keep on your team but could prove useful in the right matchup. This is important to know because this is a key factor in streaming successfully. For instance, no matter who Wade LeBlanc’s opponent is, you never want to take a chance on him. There is no strikeout potential, no ratio potential, and in his last three starts he has a 10.13 ERA.
For this piece I wanted to keep it under 10% in terms of rostered percentage. This way it ensures most if not all of the names below are available in your league.
On last October 3rd, I examined how the effects of the Happy Fun Ball could mess with ERA estimator assumptions. I was self-serving in that I wanted to see how the variables in my own ERA estimator (pERA) changed*. Once I had the new constants, I created the valuations, and Randy Dobnak came in with an estimated sub-3.00 ERA ahead of starters such as Carlos Carrasco, Blake Snell, and Shane Bieber. The rankings were there for the public to admire and they were completely ignored throughout draft season.
I probably would have ignored them also if it weren’t for Spencer Turnbull. At the end of the 2018 season, Turnbull had a 6.06 ERA and was on no one’s radar for 2019. But I had his pERA at 2.31 better than both Justin Verlander and Chris Sale. I completely blew off the rankings and paid for it. From the beginning of the season until a shoulder injury in late June, Turnbull had a 2.97 ERA, 9.2 K/9, and 1.29 WHIP. And I had him rostered on no teams.
Read the rest of this entry »
Yesterday, I listed and discussed the top 20 starting pitcher SIERA leaders. Since the entire season represents a small sample size, you should be far more inclined to focus on a pitcher’s SIERA, driven by his underlying skills, than the ratios that actually count in your fantasy leagues, ERA and WHIP. The underlying metrics fueling SIERA stabilize far quicker and account for skills pitchers have more control over. It therefore makes for a significantly better rest of season projection, even though SIERA is meant to be backwards looking, not forward looking. With that said, let’s check in on the bottom 20 pitchers in SIERA and discuss the interesting names. As a reminder, just because a pitcher finds his name here doesn’t mean you should drop him or trade him away, as the pitcher could improve his skills, pushing his SIERA down into more attractive territory.
