Author Archive

The Process: The Next Evolution in Fantasy Baseball

The Process is done. After months of writing and disagreements, the fantasy baseball guide I wrote with Tanner Bell is for sale. Simply, we researched and created the guide we would want. It’s not going to contain player capsules or positional rankings. Dozens of sources provide them. Instead, it’s going to give the reader the ability to create their own and the 2017 NFBC Main Event Champion and my podcast mate, Rob Silver wasn’t happy about the end results as he states in his intro.

Jeff Zimmerman and Tanner Bell are both awful people.

Thanks Rob. Before Rob gets to explain himself, here is the general flow of he book.

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Introducing StatCast/xStats Week(s) at RotoGraphs

From now until some point before the season starts, the focus of most RotoGraph articles will be on getting the most useful information out of the StatCast information. It’ll include as many or as few of articles to create a good understanding of the data. With tons of available information much has been written about the subject especially here at RotoGraphs. The key with this series is to cut through all the different data points (e.g. launch angle, spin rate, sprint speed) and how they measured (e.g. max, average, weighted) to find which values to focus on and which ones to ignore.

The point of this article is to provide an initial forum, via the comments, to collect and try to answer the question with any previous research. There is no need to completely recreate everything.

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What Fastball Velocity Value is Most Predictive?

Yesterday, I published an article on a few pitchers whose fastball velocity changed over the course of last season. And then my old buddy MGL showed up.

He’s right. I have so much on my plate right now, mainly my first book and a 2019 player previews, that I didn’t take it another step forward. Here are most of his answers.

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Velocity Changes During the 2018 Season

It may seem that fastball velocity gets over utilized for explaining a pitcher performance, but I don’t think it gets used enough. As I get going full steam ahead in my off-season research, I find myself always looking to see how a pitcher’s velocity held up over the season. Instead of looking up each pitcher individually, I decided to go ahead and collect 2018 fastball velocity reading for an easy reference.

For the data, I found the pitcher’s velocity for the whole season, April to June, July to October, and just September/October. The entire data dataset can be found here.

I went through the data and found some intriguing pitchers who gained and lost a few ticks. I divided up the analysis between first versus second half and first half and September. Many of the same pitchers would have made both lists. Here is the first to second half values.

Notable 1H to 2H Fastball Velocity Changes
2Hv-1Hv Pitcher Fastball Count Season Velo 1H Velo 2H Velo Sept Velo
-1.7 Stephen Strasburg FF 996 94.6 95.3 93.6 93.3
-1.2 Dereck Rodriguez FF 710 91.6 92.4 91.2 90.9
-1.1 Marco Estrada FF 1230 88.5 89.0 87.8 88.0
-1.0 Antonio Senzatela FF 976 93.6 94.4 93.4 93.1
-0.9 Tyler Skaggs FF 931 91.5 91.8 90.9 90.0
-0.9 Brad Keller FF 992 94.3 94.9 94.0 94.3
-0.8 Marco Gonzales SI 650 90.1 90.4 89.6 89.3
-0.8 Jon Gray FF 1387 94.7 95.0 94.3 94.2
1.1 Zack Wheeler FF 1295 95.8 95.3 96.4 95.8
1.1 Mike Clevinger FF 1735 93.6 93.0 94.2 94.5
1.2 Gerrit Cole FF 1617 96.2 95.6 96.7 96.5
1.2 Jacob deGrom FF 1399 96.0 95.4 96.7 96.9
1.3 Jordan Hicks SI 707 100.5 99.7 101.0 101.1
1.4 Cole Hamels FT 450 91.4 90.8 92.2 91.8
1.5 Gio Gonzalez FF 885 89.8 89.0 90.5 90.3
1.5 Lucas Giolito FF 1305 92.3 91.7 93.2 92.5
2.2 Matthew Boyd FF 904 90.4 89.3 91.5 92.4

Stephen Strasburg is the most concerning name on the list with his fastball down ~2 mph. The drop occurred after he went on the DL with shoulder inflammation.

His results also took a hit with his ERA going from 3.46 to 4.20 and his K%-BB% dropping from 23% to 19%.

Strasburg is getting in the danger zone where his fastball will start losing its effectiveness if he loses any more velocity. Here are its swinging-strike rates since he joined the league at different velocities.

Strasburg’s Fastball Swinging-Strike Rate
mph SwStr%
92 4.8%
93 7.0%
94 12.7%
95 13.9%
96 16.8%
97 14.7%
98 16.0%

The fastball starts to lose its effectiveness as it dips near 93 mph.

With the velocity drop, Strasburg will still be a good pitcher because his changeup is elite and curve and slider are decent. His issue is that he’s already been cutting his fastball usage from 73% when he entered the league to 52% last season. I think the chances of him having that elite season has passed.

One major consideration will be if he can get his walks under control. In the first half, they were at 2.1 BB/9 but jumped to 3.5 BB/9 in the second half. Spring training reports are going to matter quite a bit on how he gets valued.

Notable 1H to September Fastball Velocity Changes
SEPv-1Hv Pitcher Fastball Count Season Velo 1H Velo 2H Velo Sept Velo
-2.2 Danny Duffy FF 1044 93.0 92.9 93.1 90.7
-2.1 Chris Sale FF 957 95.3 95.1 95.9 93.0
-1.6 Corey Kluber FC 922 88.5 88.7 88.3 87.0
-1.5 Aroldis Chapman FF 679 98.9 99.1 98.5 97.6
-1.3 Bartolo Colon FT 1369 86.9 86.9 86.8 85.6
1.4 Luis Castillo FF 944 95.9 95.5 96.4 96.9
1.5 Patrick Corbin FF 630 90.8 90.5 91.1 92.0
1.6 Tyson Ross FF 1226 90.7 90.4 91.1 92.1
1.8 Drew Pomeranz FF 576 89.4 88.9 89.9 90.8
1.9 Sean Newcomb FF 1833 92.9 92.7 93.3 94.5
2.0 Mike Fiers FF 1095 89.4 88.5 90.2 90.5
2.7 Martin Perez FT 703 92.5 91.4 92.9 94.1

Corey Kluber is the name which jumps off. For pitcher going in the second round of mock drafts, an ~1.5 mph drop in his fastball throws a major red flag.

He got hit around more in the second half with his BABIP jumping from .248 to .321 while list strikeout and walk rates remained constant (22.5 K%-BB% to 22.1 K%-BB%). Kluber found a way to be effective even with the velocity loss.

My gut says something is off but I can’t find it. His steamer projection has his ERA next season back in the 3.50 range (same as 2015). so it even sees that something is not right. I’ll read some more previews as the season nears and see if I can gain a better understanding of him.


Fantasy Pitchers Ranked Using Steamer Projections

A computer program and I are back for some more abuse. After lining up the Steamer hitter projections with the Standings Gain Points (SGP) for The Great Fantasy Baseball Invitational, the pitchers now take center stage. And boy can I see some conflicts to fill the comments.

The SGP formula is from the average of the 13, 15-team Roto leagues and will soon be available in The Process (looks like Monday at the latest).

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Prorated 2018 Pitcher Roto Values

A while back, I ranked hitters if all their 2018 stats were prorated to 600 plate appearances. It’s now time for the pitchers. In all fairness, the rankings are a huge disappointment with no surprises coming through.

I adjusted the rankings for 180 innings for starters and 60 innings for relievers and no one seemed out of place. With the hitters, Raul Mondesi at the top was an attention-getter. Looking over both sets of top-25 pitchers, the biggest surprise was Joshua James and he’s not really a surprise since he dominated at the season’s end. Time to get bored.

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Update On Initial Closer Chances

Two seasons ago, I examined the chances the season’s initial closer made it the entire season without being replaced for any reason including injury. I went back and revisited the study and updated it with 2017 and 2018 results. While the initially calculated chances were low, the odds are getting even worse.

I posted to Twitter account my initial results for the last two seasons to make sure nothing was too far off. Thanks to everyone for the responses and here are the end results:
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Fantasy Hitters Ranked Using Steamer Projections

It’s rankings time so the comments are open for everyone to go batshit crazy about how a computer program and I are wrong.  We are both ready for everyone’s best shot as neither one of us gives a flying  f***.

As part of my soon to be released e-book, The Process, the Standing Gain Points formulas will be included for several league types. I took the one for The Great Fantasy Baseball Invitational, merge it with Steamer projections, and created some overall rankings.

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Two-Pitch Starters

A diverse pitching arsenal can help a starter successfully navigate a lineup several times since hitters have a harder time sitting on a single pitch. I went through the 2018 starters and found four pitcher groups who are the two ends of the spectrum. Either they rely on two pitches or have a diverse arsenal.

Many articles have been written about times through the order but the Holy Grail of research articles is the one MGL wrote a few years back. In it, he quantified how much having a third pitch helps. The research holds up even now. I took the 206 starters who threw at least 30 innings and found the percentage of pitches which were fastballs and next highest thrown. Normally, the average was around 75%. Then, I divided up the pitchers into 5% increments. Next, I subtracted the ERA from an average of their ERA estimators (FIP, xFIP, kwERA, SIERA) and here the average values. Read the rest of this entry »


Prorated 2018 Hitter Roto Values

I try not to miss examining players who had great, short seasons. An injury or time in the minors kept them off the end-of-season rankings. They flew under the radar but given a full season of playing time they stick out and could provide hidden value. Today, I’m going to start by examing the top prorated hitters.

I needed a way to value the hitters and decided to create an overall Standing Gain Points (SGP) formula from The Great Fantasy Baseball Invitational leagues. The 13 15-team leagues were set up with  14 hitters (1 C, 2 Util), 9 pitchers, and used AVG. Tanner Bell and I will be providing this formula, along with several others, in our new book, The Process, available within weeks (shameless plug).

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