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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Note: If you read this on Saturday evening, I’m likely to add a few names as I do some more research and more news rolls in.

Projecting this season’s FAAB is going to be a nightmare. In past seasons, the process seemed fruitless at times but it’s going to be even more of a mess this season. Most leagues are giving teams the same amount of FAAB to cover a third of the season that will lead to some high dollar desperate bidding. Additionally, when a league was drafted matters. For instance, I have two leagues running FAAB tomorrow. The one from early March I need to clean up (e.g. one had Trey Mancini) and the other I drafted last so I may gamble on some different bullpen arms.

In this article, I’m going to at least cover the players in demand using CBS’s (40% or less ownership) and Yahoo’s ADD/DROP rates. Both hosting sites have the option for daily and weekly waiver wire adds. CBS used a weekly change while Yahoo looks at the last 24 hours. Yahoo is a great snapshot of right now while CBS ensures hot targets from early in the week aren’t missed.

Additionally, I’m going to add anyone else I fill is appropriate.

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In my previous article, I gave an update on my Weighted Plate Discipline Index (wPDI) metric. wPDI arises from the core ingredients of plate discipline – looking only at zone rates, swing rates and contact rates.

An important distinction regarding wPDI, is that its sample size is quite a bit larger than other statistics. Many other stats are based on innings pitched, or even per plate appearance. The denominator of wPDI is pitches. While batter outcomes such as strikeouts and walks stabilize fairly quickly, wPDI can work even faster.

Let’s now take a look at the 2019 leaderboards for wPDI, to see if we can find some undervalued players.

Starting Pitchers

Above is the 2019 wPDI leaderboard for starting pitchers.

Blake Snell lead all starting pitchers in wPDI in 2019. The key to Snell’s success was his “out of the zone” plate discipline. In particular, Snell’s Outcome A (out of the zone, swung on and missed) was the 2^nd highest of all qualified pitchers in baseball. In 2019, Blake produced a K% rate of 33.3%, the highest of his career. He logged a whopping 147 strikeouts in just 107 innings pitched. Both FIP and xFIP (3.32 & 3.31 respectively) agree that his 4.29 ERA last year was somewhat unlucky.

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With most teams planning to limit the innings their starters throw, there are going to be a few middle relievers who bridge the gap to the seventh to ninth-inning guys. Because most starters will not go five innings, these bridge relievers will have the chance to accumulate a few Wins while hopefully providing decent ratios. Here are some targets.

Every season, some middle relievers go off accumulating half dozen Wins and Saves, great ratios, and over 100 strikeouts. They are more valuable than most starters and closers. The deal is that no one has a clue which middle reliever it will be, but whoever rosters them will be loving it. I decided to query a target list.
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Introduction

Last year, I introduced a new (yet simple) pitcher metric. Weighted Plate Discipline Index (wPDI) arises from the core ingredients of plate discipline from the point of view of the pitcher – control, deception, and contact.

wPDI looks at the following basic binary events:

• Was the ball thrown in the strike zone?
• Was the ball swung on?
• Did the batter make contact with the ball?

That’s all.

Weighted Plate Discipline Index (wPDI) does not look at generated bat speed, exit velocity, pitch speed, or quality of contact, etc. wPDI doesn’t even focus on walk rates or strikeout rates, or any other plate appearance result. wPDI focuses solely on the pure components of a pitch. Is the pitch in the zone? Is the batter swinging at pitches in the zone? Is the batter swinging at pitches outside of the zone? Is the hitter contacting the pitch?

That’s all.

In this series of articles, I will be refining and expanding upon what I had started last year. I will look at wPDI’s effectiveness and predictability. Along the way, I shall highlight both pitchers and hitters who catch our eye based on great (and poor) plate discipline performance.

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One of my Launch Angle Podcast partners, Rob Silver, brought up how if there is a universal DH, the NL pitcher will no longer face ineffective bat-wielding pitchers. Simply, pitchers can’t hit. Last season in 4789 PA, National League pitchers hit for a combined .126/.157/.160. Our own Dan Szymborski continued the discussion to see if dominating pitchers hitting was a repeatable trait. I’m going to go a different route to investigate, using Dan’s information, how a pitcher’s projection would change going to an American League team (effectively including a DH) and this number affects a pitcher ranking.

I’m going to start off saying to not take any of the following information as the gospel truth. I’m trying to achieve a better projection that’ll be closer to the final outcome. Each stat and step in the process can be nitpicked along the way. I’m not even sure if the following method is the best way but it’s a way. I’m trying to move the discussion from “The DH will be a try breaker for me when drafting” (quote from a podcast I heard) to actually putting some number behind the possible changes.

Also, I’m not here to argue on why Jacob deGrom started out as the 8th ranked starter and he’s now 9th. I just collect a projection set. Anyone who uses stats to generate their projections will have their own secret sauce. I have my own. I just need a projection framework and live with it. Here is how I set it up.

I downloaded the 2020 ZiPS projections from here at FanGraphs. I used the ZiPS values since Dan created them and I’ll be using the inter-league adjustments provide in his article.

Then I changed each pitcher’s stats using Dan’s 2019 variables.

Variable: Change

• BB%: +4%
• K%: -5%
• AVG: +.007
• RC/G: +13%

I just adjusted the pitcher’s projected stats by the above values and created a hits estimate from the AVG with few assumptions.

NL pitcher innings projections have two offsetting values that could also be in play. The worse results could lead to fewer innings thrown (i.e. early hook) and the pitcher’s value could drop. On the other hand, the times a pitcher nearing his pitch limit will be replaced by a pinch batter will disappear. One of the two factors will likely dominate

Next, I used the 2019 12-team SGP (Standings Gain Points) formula from The Process to create pitcher valuations. The SGP value is the expected jump in the standings if that pitcher’s stats are added to a team’s stats. Here are results from the final top-40 starting pitcher using the SGP formula and ZiPS projections (I’m not sure why the TJS pitchers are still included but I don’t get paid the big bucks to know such things).

The changes are significant once all three factors (WHIP, ERA, strikeouts) are factored in. While the rank changes by just one or two with the top-10 or so arms, the difference becomes significant around pick 20 with moves of four spots. Maybe this change is a tie-breaker for some owners, but if an owner gains an extra ~1 SGP from all nine pitchers, it becomes nine spots in the standings. I think every owner would take those extra spots.

Just eyeballing the differences, it’s ~0.40 increase in ERA and 0.04 bump in WHIP to go with the 5% drop in strikeouts. The near half run increase in ERA will scare off quite a few owners by itself. Other owners will get blow off the possible changes, but in my current opinion, they will be playing catch up if they ignore them.

Again, don’t take my word for it … I’m still coming to grips with Lance Lynn possibly jumping Patrick Corbin. I could be wrong with these calculations but hopefully, some other analysts will step up and perform the calculations. The possible change in production is likely the biggest valuation change with half the pitchers facing legit MLB hitters instead of the irrelevant pitcher.

Let’s talk about the best prospect fastballs! These are the 9 pitchers with at least a 70 grade FB – Present (FBP) and 50 or higher FV grade for those with a 70 grade FBP.

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While I had little luck finding the next Lucas Giolito, he still intrigued me. He was possibly the worst major league starter in 2018 (6.13 ERA and 1.48 WHIP in 173 IP). Last season, he remade himself by throwing harder (avg FBv from 92.4 mph to 94.3 mph), throwing more strikes (4.7 BB/9 to 2.90 BB/9), and reworking his pitch mix (dropped the sinker and curve).

The problem is that standard projection systems still incorporate the previous three or more results which hurt his projection. Our auction calculator (Steamer) ranks him as the 45th pitcher while he’s going as the 14th pitcher in the NFBC. Fantasy owners knew to reset his projection but to what? I decided to create a projection system called the GM (Giolito – Marte) based only on the previous season results. Nothing more.
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The following is the second part of my 2020 Tout Wars Head-to-Head Points League recap. You can read Part I of my recap here.

For the second straight year, I had the honor and privilege of participating in one of the most prestigious fantasy baseball industry leagues – Tout Wars (toutwars.com). This was my very first live Tout Wars auction. Due to the COVID-19 outbreak, we drafted online on the Sunday of March 15, 2020.

In Part I of my recap, I discussed the league rules, some of the homework that I had done on last year’s auction results, and how I obtained my auction values. I also talked about some of my other adjustments made due to the postponing of the MLB season.

Part II of my recap will be different than the typical recap article you tend to see. It will certainly differ from my usual writing style.

In today’s article, I will go through some of the intel that I had gathered on my opponents. I will dictate to you what I was looking for from the other touts and how I picked up on particular strategies during the auction. I will talk about what went right for me at the auction table and what went wrong. Finally, I will give a brief overview on my player selections.

The Touts

Well, I’m not sure that I would call members of the Tout Wars Head-to-Head Points my enemies. However, they most certainly were my opponents … at least for that Sunday afternoon in March. The quote above has appeared in folklore from many cultures, and of course, was one of the great lines of the movie “The Godfather.”

Fantasy baseball is largely about the numbers. If you often read my articles, you likely already know the importance that I place on projections and valuation.

Almost as important … perhaps even more important … is knowing your opponents. It is an advantage to be aware of the types of players that they bid on, how high they press bids, whether they nominate players they want to buy, the typical construct of their fantasy squads, etc.

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