Getting back on the spin rate train

It's been about a week since I first wrote in this space about four-seam fastball spin rates. So today, I am jumping back on the spin rate train and presenting more data that is available to all from the baseballsavant.mlb.com website.

Once again trying not to hurt myself, pull a hammie or break a hamate and/or injure myself in any way as I jump on the train. Too close to the start of a new season for any reporter setbacks.

Today let's look at breaking pitches - sliders, curveballs and cut fastballs, or what are known as "cutters" in the game. A cutter and slider have similar movement but are considered different pitches. Sliders have more downward and horizontal break. Cutters have less movement but later break, which can be hard for the hitter to adjust to and square up.

The earlier blog entry noted that spin rate is presented in RPMs - revolutions per minute after the baseball is released. Two of the same pitches, thrown at the same velocity but with different spin rates, will end up in different places. A four-seam fastball, thrown with backspin, has many RPMs. There is an aspect to this we call "active spin" or "spin efficiency." That is essentially the percent of the spin that actually impacts the ball's movement. This is quantified as a percentage. Someone with a 90.0 rating is getting 90 percent efficiency of a possible 100 percent in their spin.

I've observed that spin efficiency is lower for curveballs, generally, than for four-seam fastballs. It is lower for sliders than for curves and lower yet for cutters. Must be harder to be as efficient with pitches that hurlers need to manipulate somewhat.

As a reporter who is much more beginner than expert when it comes to spin rates, how the data is used and what it all means, I turned again to someone for help. I sought out Alex Fast, an associate producer at Major League Baseball and the vice president of PitcherList.com. He helped point me in the right direction in finding data and explaining much of what I found.

Again, please keep in mind that we are presenting two numbers here, the spin rate of a pitch and also the active spin or spin efficiency. Of the two data points, the efficiency is the bigger and more important number here.

"Efficiency is going to be really big and then spin is going to be secondary," Fast told me. "When it comes to spin efficiency, you can have poor spin efficiency numbers, it's just, how do we build an arsenal around whatever that pitcher is? For example, if the Orioles traded for someone who has 60 percent spin efficiency on his fastball, some people might think, 'Why would they be getting that guy?' There is probably something else in his arsenal that reflects that."

In looking at these pitches today, I will list where O's pitchers rank in efficiency first with each pitch. In curveball efficiency among pitchers that threw at least 100 pitches last year (all pitches, not just curves), 301 pitchers were rated, from No. 1 to No. 301. Here is where several O's were ranked.

38 - Dean Kremer
64 - John Means
95 - Travis Lakins Sr.
147 - Jorge López
171 - Alex Cobb
195 - Keegan Akin

So the first three rank in the top third in baseball in active spin on the curveball. Kremer ranks in the top 13 percent. No other pitchers were listed for curveball spin efficiency. It could be they didn't have enough data to rank those pitchers, but I'm not completely sure on that.

In rankings for curveball spin rate, Travis Lakins Sr. was No. 77 and tied with lefty Bruce Zimmermann. Lefty Keegan Akin was No. 122, Alex Cobb No. 139, Dean Kremer No. 260, John Means No. 264 and Hunter Harvey No. 329.

The average spin rate on a curveball in the majors in 2020 was 2,532. Lakins and Zimmermann were at 2,727 and Akin 2,606.

Here is where O's pitchers rated in slider efficiency among 367 pitchers that were included in the 2020 rankings.

20 - Paul Fry
31 - Shawn Armstrong
132 - Cole Sulser
135 - Keegan Akin
197 - John Means
270 - Tanner Scott
320 - Dillon Tate
327 - Bruce Zimmermann

Looking at slider raw spin rates, Armstrong was No. 23, Fry No. 30, Scott No. 34, Zimmermann No. 79, Means No. 162, César Valdez No. 186, Tate No. 194, Akin No. 236 and Sulser No. 240.

The average slider spin rate last year was 2,438. The top three O's were well above with that, with Armstrong at 2,840, Fry 2,802 and Scott 2,778.

Last year Fry posted a 48.4 percent whiff rate and Scott a 43.1 percent whiff rate on sliders. That is swings divided by swings-and-misses.

Here is where O's pitchers rank in cutter efficiency. Since fewer pitchers throw cutters (they were thrown just 6.6 percent in the major leagues last year) or at least the pitches that Statcast classifies as a cutter, there are only 131 rated for their efficiency with that particular pitch.

53 - Travis Lakins Sr.
69 - Shawn Armstrong
75 - Dean Kremer

In cutter spin rate data, Armstrong is No. 20, Kremer No. 41, and Lakins No. 67 among 154 pitchers rated for cutter spin rate.

If you are beginning to think this all may just be too much to try to process or make sense of, you may well be right. How much one chooses to dig into or believe in the data is up to each individual. We can completely ignore or discount this and believe me, you will still be able to watch games and enjoy them every bit as much as you ever have if you do exactly that. I'm just making my attempt to learn about some of this data and understand it a bit better.

I think some of this translates to the analytics element. A team analyst may meet with a pitcher and point out that his slider is producing much better data than his curveball but then note that pitcher throws his curveball much more than his slider. Maybe the pitcher didn't realize the slider is a better quality pitch for him. It can help pitchers adjust their pitch mix to become more efficient and effective. This is just one way that taking this data and using it can help a pitcher get better.

No doubt the teams have much more data than is publicly available, and many ways to use it. They hire people to spend their days working on such things.

Scouts for years used the "eye test" and yes, no doubt we can all watch a pitcher and note what appear to be his best pitches. Surely the batter results tells us a big story as well. Maybe just not the whole story. This data provides more ways to look at and note it.

If you choose to do it.