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Quantifying Slider Deception (Fantasy Baseball)

May 1, 2020

Felix Pena finds himself near the top of the list with a sneaky-good slider.

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In this post series, I am attempting to find which pitchers in the Majors are most deceptive without making any subjective judgment. This is not an easy thing to do, and I cannot say that this is a perfect way of going about this, but I do think it is interesting and unique. Check out my post on fastball deception here. You will find a more full explanation of the ideas behind this analysis in there.

The way we do this is with pitch clustering. What this means is that we want to isolate an individual pitch, and then categorize pitchers into groupings based on how they throw the pitch. If we have a group of pitchers who all throw a very similar slider, but some are getting much better results than others, we can then surmise that there must be something else going on – namely deception.

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The Data

This is a bit tougher to do with sliders than fastballs, as just using velocity and spin rate was not enough. I also used horizontal movement and vertical movement, so we had four data points to cluster with.

The Clusters

The average slider has a velocity of around 85 miles per hour, with a spin rate of around 2,440 rotations per minute, and a horizontal movement of around six inches and very little vertical movement.

I decided on five clusters after doing some testing. Here is how they broke down:

Cluster 1: Low velo, high spin, high horizontal movement
Cluster 2: High velo, high spin, moderate horizontal movement

Cluster 3: Low velo, moderate spin, moderate horizontal movement
Cluster 4: High velo, moderate spin, low horizontal movement, high vertical movement
Cluster 5: Moderate velo, low spin, low horizontal movement, high vertical movement

Your best sliders are in clusters 1 and 2. They have the highest spin rates and highest movements, with the velocity difference being what separates them. Sliders in the first cluster average 81.5 miles per hour, while cluster two sliders come in at 86 miles per hour.

Here are the most common pitchers in each cluster.

Cluster 1: Jakob Junis, Chris Sale, Trevor Bauer
Cluster 2: Luke Jackson, Marcus Stroman, Brad Keller
Cluster 3: Matthew Boyd, Patrick Corbin, Dylan Bundy
Cluster 4: Jacob deGrom, Justin Verlander, Jon Gray
Cluster 5: Robbie Ray, Caleb Smith, Shane Bieber

Results

For each cluster, I will show you the top ten in terms of CSW rate (called strike + swinging-strike rate) on their sliders. The fifth column is that cluster’s average CSW rate, and the sixth column is the difference between the pitcher’s rate and the cluster average.

Cluster 1:

Cluster 2:

Cluster 3:

Cluster 4:

Cluster 5:

Top 25 Overall:

Some surprising names ending up on top, with guys like Felix Pena and Kyle Gibson showing some sneaky-good sliders. You have your usual suspects as well, with a bunch of elite relievers and Max Scherzer.

If you want to dig into the data yourself, you can find it here.

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Jon Anderson is a featured writer at FantasyPros. For more from Jon, check out his archive and follow him @JonPgh.

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