Wild Windups: Do They Help?

Earlier this week, I found most of Tanaka’s struggles occur with men-on-base. What I didn’t know if these differences were predictive or due for regression. After diving into the numbers, struggles with men on base aren’t exactly predictive except for those with extreme windups.

The narrative concept behind this study is that a pitcher has a windup talent level and a throwing from the stretch talent level. I’ve always thought Daniel Mengden’s great windup would keep hitters off guard.

 

He loses all the deception from the stretch. My theory has been borne out with a career 4.99 FIP with runners on base and 3.42 FIP with the bases empty. Joey Lucchesi is another pitcher with a unique windup and he has a 3.40 FIP with no runners on base but it jumps to 5.14 with runners on. The windup advantage for these two pitchers is an obvious item to point to when explaining their stats.

While Tanaka displays some windup deception, it’s not really anything out of the norm so it’s tough to single him out as having an advantage.

If fantasy owners knew the pitchers who had this difference, they could quickly pinpoint why the pitcher’s ERA and ERA estimators differ. FIP and its various one-offs don’t know when the damage occurs. A pitcher can be a 2.00 ERA estimator pitcher with no one on bases a 4.00 one with runners on. Since the lack of strikeouts and extra walks occur more often with runners on, the runs allowed will be higher than expected.

Having this trait isn’t a death wish for a pitcher since they can be great out of the windup and average out of the stretch. Enough on the narrative, now onto the math.

The first study was to take the difference in stats from throwing with runners on and not in back-to-back season (min 250 batters faced with the based empty). Then I found how these two differences correlated from one season to the next. The results weren’t pretty using 1336 samples since 2002.

Year-to-Year Correlation Between Differences With Runners On Base and Not On
Stat R-squared
BB% .060
K% .015
FIP .004
vs. wOBA .003
vs. SLG .002
vs. ISO .000

The only stat which shows just a bit of year-to-year correlation is walk rate. This makes since pitchers don’t want to throw a meatball with runners on base. Still, an r-squared of .06 is worth a midnight Tweet.

The difference averages out to a 1.5% BB% increase with runners on base. For reference, here are all the average changes these pitchers saw when a runner is on base and not.

Average Stat Change With Runners On Base and Not On
Stat Average Change
BB% 1.5%
K% -1.3%
FIP 0.13
wOBA .008
SLG .008
ISO .008

On average, pitchers throw a bit worse from the stretch. At least this finding follows our narrative.

One other comparison I ran was to match up the stats when runners are on base and compare them. I did the same thing when there are no runners on.

Year-to-Year Correlation With Runners On Base and for No Runners On
Stat Bases Empty Runners On
K% .54 .49
BB% .35 .24
FIP .22 .12
wOBA .12 .08
SLG .11 .06
ISO .09 .03

I’m not surprised one bit to see lower correlations with runners on since the pitchers faced 41% more batters with no one on than with runners on.

While the differences don’t form a good correlation, the year-to-year stats are more predictable. The problem is that besides strikeouts and walks, the correlations aren’t strong once batted ball data is added.

Circling back to Tanaka, I’d expect his struggles with runners on base to drop, especially his high vs. SLG. There just doesn’t seem to be much of a difference in his hard-hit rate from the windup and stretch.

Now, he may see some walk rate spike continue as it has some stickiness.

Since previous stats can’t just predict the stretch and windup differences, fantasy owners may need to do a little scouting. I asked my Twitter followers which pitchers have a unique windup which could add pitch deception. Here are all the pitchers submitted with video grouped by the windup’s uniqueness.

Group 1

Joey Lucchesi

 

Clayton Kershaw

 

Johnny Cueto

 

Alex Wood

 

Group 2
Tyler Anderson

 

Carson Fulmer

 

Chris Sale

 

Mike Clevinger

 

Kenta Maeda

 

Group 3
Rich Hill

 

Marcus Stroman

Alex Cobb

 

Yu Darvish

 

Zack Godley

 

After having a couple other authors help verify the groups, I found the career results for these pitchers with and without runners on base.

Pitcher Results Depending on Uniqueness of Windup
Bases empty Runners on Difference
Name K%-BB% FIP xFIP K%-BB% FIP xFIP K%-BB% FIP xFIP
Group 1 Joey Lucchesi 24.4% 3.40 2.72 0.0 5.86 5.14 -22.8% 2.46 2.42
Daniel Mengden 17.2% 3.42 3.71 0.0 4.99 5.58 -12.7% 1.57 1.87
Clayton Kershaw 22.9% 2.39 2.78 0.2 2.99 3.13 -4.6% 0.60 0.35
Alex Wood 15.8% 3.40 3.41 0.2 3.12 3.45 -0.5% -0.28 0.04
Johnny Cueto 15.6% 3.72 3.64 0.1 3.80 4.12 -5.1% 0.08 0.48
Average -9.1% 0.89 1.03
Median -5.1% 0.60 0.48
Group 2 Tyler Anderson 14.1% 4.27 4.03 0.2 4.00 5.08 1.4% -0.27 1.05
Carson Fulmer 1.2% 8.52 6.89 0.0 5.79 5.99 3.7% -2.73 -0.90
Mike Clevinger 11.7% 3.84 4.31 0.2 3.89 3.99 4.2% 0.05 -0.32
Chris Sale 23.7% 3.00 3.02 0.2 2.89 2.90 0.1% -0.11 -0.12
Kenda Maeda 21.3% 3.17 3.41 0.1 4.54 4.21 -6.5% 1.37 0.80
Average 2.4% -0.77 -0.07
Median 2.6% -0.19 -0.22
Group 3 Rich Hill 14.3% 4.14 4.29 0.2 3.81 3.93 0.9% -0.33 -0.36
Marcus Stroman 13.9% 3.48 3.35 0.1 3.84 3.57 -2.5% 0.36 0.22
Alex Cobb 15.0% 3.74 3.35 0.1 3.78 4.09 -6.8% 0.04 0.74
Yu Darvish 19.3% 3.82 3.49 0.2 2.77 3.01 2.9% -1.05 -0.48
Zack Godley 18.8% 3.70 3.39 0.1 4.36 4.11 -11.1% 0.66 0.72
Average -3.3% -0.06 0.17
Median -2.5% 0.04 0.22
Groups 2 & 3
Average -1.4% -0.20 0.14
Median 0.5% -0.03 0.05

The first group’s results are what we expect with the windup results being better. The FIP and xFIP values are about one point better from the windup than stretch. As for the other two groups, the windup’s deception doesn’t seem to matter. In this quick-and-nerdy study, only the most extreme windups seem to throw hitters off.

It’s time to put all the information into one final money quote. Predicting different pitching results with and without runners on base is minimal at best except for pitchers with the most unique windups.





Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

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mrdog61member
5 years ago

It worked for Bugs Bunny

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