Justin is running his annual Too Early Mocks and the wonderful Smada has once again compiled the average draft data for our perusal.

The Top 3 SPs: Jacob deGrom, Shane Bieber, Gerrit Cole – deGrom went 1 in one league and Cole went 4 in another, but otherwise they averaged 7.7, 9.2, and 10.3, respectively. It’s not that I’m against the hitters going top 6 (Betts, Acuña, Tatis, Trout, Soto, and Turner), but I don’t understand how the mega aces aren’t more often in the top 3. I feel like the community at large is pushing pitching up (and not just the NFBC ecosystem), but the best of the best still don’t go high enough as far as I’m concerned.

Dinelson Lamet 53.7 ADP – He was unquestionably excellent as he flipped his pitch mix to throw the slider 53% of the time and his fastball was the best we’ve ever seen it, but he’s still at best a two-pitch guy and ended the season with a biceps injury that cost him the playoffs. That said, his slot as the 19th starter off the board matches where I put him in my initial rankings. Short of developing a third pitch, my biggest questions are whether or not the fastball can remain a plus offering and if he can continue to keep the ball in the yard – those are no doubt related as the fastball improvements played a big role his 8% HR/FB rate.

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Introduction

The key to succeeding in fantasy baseball:

Maximize the value of your accumulated roster.

At the start of a draft, each fantasy owner is handed a set of draft picks. Each owner receives a 1^st round selection, a 2^nd round selection, a 3^rd round selection, and so on. If your league chooses to hold an auction rather than a more traditional serpentine draft – each team is handed $260 at the auction start. Players are then purchased throughout the auction with the use of these finite funds.

The key to gainfully drafting is not to draft a 3^rd round player in the 3^rd round, or a 9^th round player in the 9^th round, etc. The key is to draft a 3^rd round player in the 10^th round, and a 9^th round player in the 20^th round.

In an auction, if you purchase every player at his projected value, you will have paid $260 of auction dollars for $260 of value. What you will have is an average team. You won’t finish last, but you won’t finish first. Instead, with your $260 – you need to buy some $290 or $300 or $310+ of total value.

The key is to make a “profit” on as many roster spots as you can. The goal is to purchase players at bargain prices.

I have asked this question before – but it is worth asking every now and again. Suppose that you competed in an NFBC fantasy baseball auction back in July this season.

Which player was the better purchase?

Bryce Harper (OF, PHI)

OR

Andrew McCutchen (OF, PHI)

Before opining on the better Philly outfield purchase of 2020, let’s take a look at their final 2020 stat lines:

On the surface, it seems like a pretty obvious answer. Harper had more HR, SB, R and a better batting average than McCutchen. He had just one fewer RBI.

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After focusing the 2021 prep on hitters for the last couple of weeks, it’s time for pitchers to take center stage. There is no way to hide that the following is mostly a data dump with a small bit of analysis. Welcome to mid-October 2021 draft prep.

Single Season Projections

These projections are about as simple as it gets. It takes a pitcher’s 2020 results and projections the pitcher going forward based just on those stats. With some pitchers completely changing their pitch arsenal, I find these projections are a better evaluation tool than multi-year averages. For a reference, here is the full write up on how they are created.
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This month last year, Connor Kurcon of Six Man Rotation set out to quantify the location aspect of command (or “LRP”). By establishing an accounting system that credited and debited pitchers for changes in ball-strike counts based on the attack zone of and hitter’s disposition (take? swing? ball in play?) for every pitch, he effectively created an alternative to Pitch Value (PVal) that rewards optimal movement through ball-strike counts but with much more pitcher and hitter context.

His findings are as you’d expect: Jacob deGrom and Justin Verlander lead the pack, with Gerrit Cole, Max Scherzer, and Clayton Kershaw not far behind. Other budding aces like Jack Flaherty and Mike Clevinger pepper the list, and some pleasant surprises (such as Brendan McKay, Caleb Smith, and, for those still thirsting, Jake Odorizzi) are scattered throughout as well. Out of the bullpen, newly anointed relief ace Nick Anderson led the pack followed by the underrated Emilio Pagán, breakout reliever Giovanny Gallegos, and others.

Near the end of his post, Kurcon includes a subhead dedicated to Kyle Hendricks where he highlights how Hendricks, widely respected as a command artist, fares lukewarmly by measure of LRP. He then reminds us “LRP doesn’t paint the full picture of command.” True that.

Fortunately, Kurcon has left the door open for me to tie up loose ends with find Gs I’ve been meaning to write up for a couple of months now. Never fear, Hendricks is the command artist we know and love — it’s just that he relies heavily on incurring contact in optimal pitch locations. It is a needle very few pitchers can thread, but Hendricks does it masterfully.

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Introduction

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:

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

Introduction

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:

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

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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.
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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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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.

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Read first before freaking out

I started digging into pitch velocities and documented everyone who has changed. Two trends immediately appeared. The overall velocities were down and a few pitchers experienced major drops.

Normally in Spring Training, teams build a pitcher up to their maximum velocity and then start increasing the innings. At this point, all starters should have been ramped up to a full workload with their next start being in the regular season. Many don’t seem ready.

First off, I’m a little suspect of the velocity reading. Back in 2017, MLB installed new pitch-tracking systems and the velocities were high. A new system has been installed (Hawkeye) so something will likely be off. It is the MLB who can’t find a home for a team and decides to expand the playoffs with the season starting … that day. MLB going to MLB.

A second possible cause could the unique ramp up to the 2020 season. Teams have implemented different approaches to keeping their pitchers ready. Some of the velocities are down 5 mph from two separate parks. Maybe the pitchers are still worn down from the long postseason and four-month quarantine. Of the cameras are off. Or both.

Fastball velocities are down for a reason, but the cause(s) remains unknown. Fantasy owners need to remain calm and hopefully, in a few days, the truth will be known.
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