Pitch Movement, Part II: Sweet Seams (Are Made of This)

March 15, 2020 • Analysis

In Part I, we quickly reviewed how spin creates movement via Magnus force and the different characteristics of a pitch's spin that alters its impact. Here in Part II, we're going to look at the role the seams play in determining pitch movement.

Laminar Express: Theory vs Reality

Laminar flow sort of entered the baseball vernacular thanks to a January 2012 post at The Hardball Times by Dr. Alan Nathan that took a hard look at a Freddy Garcia pitch to explain its movement. In the course of describing it, he offered an extensive explanation of the results of experiments undertaken by Professor Rod Cross that illuminated a laminar-turbulent gradient effect. I recommend reading it and trying to wrap your head around it, even going down the rabbit hole of links he provided, but if you don't have time for that, Cross published a YouTube video that amounts to a crash course:

The criminally short version is this: if you can create a persistent smooth patch on the leading surface of a baseball, it creates a laminar-turbulent air flow gradient, and the ball's flight will deflect away from the smooth patch.

For a while, Trevor Bauer and Driveline Baseball believed this gradient influenced the flight of a special two-seamer, but that always struck me as curious because all video of this special pitch appeared to show the ball moving toward the smooth patch.

When Barton Smith wrote a post about how Trevor Bauer's Laminar Express two-seamer might work, Driveline Baseball paid him a visit. The initial results showed the effect, but it took several more posts and a realization about the spin axis itself before the explanation truly fit with previous findings. He uncovered a surprise: the magic of the smooth patch appeared to be what it meant about the location of the seams rather than the supposed laminar-turbulent gradient.

The key appears to be putting and keeping a seam in a location that causes boundary layer separation as early as possible on one side of the ball, which tends to delay boundary layer separation on the opposite side thanks to the ball's unique seam pattern.

PIV seam separation.
Smith's PIV data for a ball moving straight up. The seam on the left creates turbulence that delays boundary layer separation, and the seam on the right causes boundary layer separation. An asymmetrical wake is created, indicating a force to the left. (Source: baseballaero.com, used with permission.)

Enter: Seam-based Wake Effects

Was this the first observed and explained seam effect? Only kind of because, of course, Dr. Mike Marshall published a description similar to this in 2003 in Chapter 19 of his online book:

With two figure eight patterns sewn together, baseballs formed four loops. I determined that baseballs could rotate in such a manner as to have one of these loops constantly on its leading surface. In this way, this loop could create a circle that constantly collided with air molecules. I call the circle that this loop creates, ?The Circle of Friction.?

That sure sounds an awful lot like what's going on with the Laminar Express, doesn't it? Further reading of Chapter 19, however, fails to reveal where exactly The Circle of Friction should be, leaving the reader with nothing more than "different places ... on its leading surface". At best, Marshall's was a partial explanation.

This seam shifted wake effect is somewhat possible with a standard two-seam orientation and some gyro spin, but that isn't the only way to use a seam to cause early boundary layer separation. Smith was able to tweak the seam orientation and create this effect without any gyro spin. He explained it in a short video that appears to reveal The Circle of Friction around a smooth patch. While spinning, it looks a lot like the ball that Cross used to demonstrate this effect.

The Circle of Friction
A baseball spinning quickly, showing The Circle of Friction on the right side of the ball.

If simply changing the seam orientation can create The Circle of Friction shown above, where else can we put seams to create similar effects?

Smith asked himself this same question and very quickly produced a couple of orientations that produce an effect similar to a scuff on the ball. He called these two pitches: scuffball and looper. If you've ever seen a red-dot slider or tried to learn to throw one, they might look a little familiar to you.

A looper puts a seam near a pole of the spin axis; imagine the Laminar Express shown above with a smaller smooth area. A scuffball puts a seam directly on a pole of the spin axis (and specifically not at the other pole); imagine the Laminar Express shown above with the smooth patch shrunken all the way out of existence.

Both pitches create a rough area at or near one of the poles of the spin axis that acts like just like a scuff. The rough area creates an early and significant boundary layer separation, shifting the wake and creating movement away from the rough area.

Now remember from Part I how gyro shift changes the effective spin axis. A change in spin axis changes the leading surface of the ball, which changes what's happening on the hemisphere line -- the "edge" of the ball's leading surface. With a rough area at or near one of the poles, a change in effective spin axis also changes the effective location of the rough area.

In other words, in the same way that a change of direction alters spin effects, it can also alter seam effects.

In the video below, you'll see a simple demonstration of how the hemisphere line (indicated by the green lines) moves around the ball as the ball's trajectory (indicated by the blue arrow) changes. This spin axis remains mostly fixed, and pitches don't actually have big changes in direction, so we're talking about relatively small changes that result in a couple of inches of more or less movement.

Consider a scuffball with a little bit of gyro that moves the rough area forward on the ball's leading surface. The rough area will not cause as dramatic a boundary layer separation at first because it isn't at the edge, but as the rough area forces a change of direction, the edge effectively moves forward toward the rough area allowing it to create a more dramatic boundary layer separation resulting in a bigger shift in the wake and more movement. This is one way to create late break!

Magnus force complications

By now, you should know that it's still not that easy. Smith's preliminary research on the looper revealed something extremely curious and entirely unexpected. At 90 MPH with 3:00 tilt and no gyro at 1200 RPM, a looper with the loop on the bottom adds about 1.5" of sideways movement on average while a looper with the loop on the top subtracts about 3" of sideways movement.

Looper locations at 90 MPH.
Relative looper movement at 90 MPH, 1200 RPM, 3:00 tilt. Black: normal 2-seam orientation, control. Orange & Red: loop on the bottom. Blue & Green: loop on the top. (source: baseballaero.com, used with permission)

Think about that for a minute. In addition to the wake effect from the loop, a looper can positively or negatively impact the Magnus effect depending on which side of the ball the loop is on!

The same pitch with standard two-seam orientation was already at 100% Magnus efficiency. Somehow, a looper with the seam on the bottom -- still 100% Magnus efficient by all current definitions -- caused it to move more than a 100% efficient pitch moves.

More research is needed at higher RPM and different velocities, and I both welcome and invite that research because, frankly, that's the most ridiculous thing I've ever heard about pitch spin.

Why on earth would one add to Magnus effect while the other substracts from it? Smith has told me that he has a suspicion that one of the effects will increase and the other effect will decrease with increased RPM, and I think I know what we'll see.

The loop on the bottom of the ball creates an upward force that reduces the gyro shift caused by gravity. The loop on the top creates a downward force that increases the gyro shift caused by gravity. In other words, the bottom loop allows the pitch to spin more efficiently over the entire distance of the pitch, and the top loop reduces efficiency practically as soon as it is released.

The above is specifically true for pitches with 3:00 tilt or 9:00 tilt, but the same driving principles would apply to any looper or scuffball in terms of Magnus efficiency, at least theoretically.

The Take-Away

Depending on how well you've followed everything up to this point, the next sentence may or may not change your entire perspective on pitch spin.

Pitches with different movement patterns can have identical velocity and spin characteristics.

Stated that way, it's pretty crazy, but what if you think about it this way:

Pitches with identical velocity and spin characteristics can have different movement patterns.

Somehow, even though it says the exact same thing, the second version is a little bit more intuitive, isn't it?

For example: a Laminar Express, a looper, and a scuffball can all be thrown with the same velocity (90 MPH), same spin axis (12:00 Tilt w/100% Magnus efficiency), and same spin rate (2250 RPM) as a two-seam or four-seam fastball, but each produces a unique movement pattern.

The difference between these pitches is merely the seam orientation relative to the spin axis. This means -- and has always been true -- that seam orientation is a vital characteristic of pitch movement.

In Part III, I will get into how to describe seam orientation and discuss the pros and cons of different approaches. We've already decided to change a few things since Smith published the post we co-authored on his blog.


Pitch Movement, Part I: You Spin Me Round (Like a Baseball)

February 28, 2020 • Analysis

When I originally posted about pitch spin 11 years ago, there weren't many readily available sources of information on pitch spin beyond the basics of Magnus force. Back then, a discussion of gyro spin was somewhat advanced. It’s safe to say that, in the years since, the number of resources and the depth of topics have multiplied.

Let's quickly review what is currently "known" about Magnus force as it relates to pitching, and then we'll cover some advanced concepts before wrapping up Part I.

Magnus force basics

Magnus force is proportional to the rate of spin and the mathematical square of the velocity. At the same spin rate, faster pitches experience a greater Magnus force than slower pitches. At the same velocity, pitches with more spin experience a greater Magnus force than pitches with slower spin.

Magnus force is greatest when the spin axis is perpendicular to the path of the pitch. An axis that is not perpendicular to the path of the pitch has some amount of gyro spin. The more gyro spin there is, the smaller the Magnus force.

Magnus Effect diagram

A fastball with pure backspin creates a Magnus force straight-upward, directly opposite to gravity. A curveball with pure topspin creates a Magnus force straight-downward, in addition to gravity. These are the only two pure examples that exist because their spins do not result in a change of direction that causes a Magnus shift.

Gyro spin basics

Before getting into Magnus shift, here's a quick gyro spin primer. If you take a fastball with pure backspin and turn it left or right (like a car, not like a doorknob), you have introduced gyro spin to the pitch. The spin axis is no longer perpendicular to path of the pitch.

The more the spin axis is turned, the greater the reduction in Magnus force. If you turn the ball a full 90°, the spin axis is then completely parallel to the path of the pitch -- spinning like a football -- and the pitch becomes a pure gyro ball with zero Magnus force.

Every spin has a Magnus efficiency associated with it. On the two extremes are a purely perpendicular spin axis (with maximum Magnus, zero gyro) and a purely parallel spin axis (with zero Magnus, maximum gyro). "Spin efficiency" and "active spin" are both terms that have been used to describe Magnus efficiency. (I prefer "spin efficiency" because, frankly, all spin is active and "spin efficiency" has "efficiency" right there in the name!)

If you're into trigonometry -- and let's be real, who isn't? -- you can play around with how many degrees of gyro spin match up with what percentage of Magnus efficiency.

Magnus shift and gravity

The basic idea boils down to this: while the true spin axis remains constant relative to the pitch's initial release, the Magnus-effective spin axis changes as the pitch changes direction. This change in the effective spin axis is what I call Magnus shift.

This effect was described by David Kagan in The Hardball Times at FanGraphs a little over 2 years ago. Kagan used a lot of diagrams and illustrations that I don't feel comfortable stealing for this post. I highly recommend that you hop over there and read it, and I'll briefly offer my own words in the following paragraphs.

Kagan's discussion focuses on a pitch with pure gyro spin, which checks in at 0% spin efficiency. As gravity pulled it down and some gyro spin became side spin, the spin efficiency improved from 0%. The Magnus shift increased the spin efficiency of the pitch.

Imagine throwing a pitch with pure gyro spin out into the Grand Canyon. As it falls into the canyon, the true spin axis remains constant, but the effective spin that was initially gyro spin increasingly becomes side spin. Eventually, the pitch moves straight down and all of the initial gyro spin is then side spin. When thrown to a catcher from the mound, however, the same pitch simply does not have the time and space for gravity to dramatically alter the pitch's direction, resulting in a much, much smaller effect.

If we start with a pitch with pure side spin at 100% spin efficiency, the gravity-induced Magnus shift results in some of the side spin becoming gyro spin, and spin efficiency deteriorates from 100%. In this case, the Magnus shift decreased the spin efficiency of the pitch.

In Kagan's article, he focused specifically on this gravity effect for a pitch with pure gyro spin and found that, for an 85 MPH pitch with 1500 RPM of pure gyro spin, this effect contributes only 1/2" of movement.

The Magnus shift due to gravity is incredibly small and likely isn't worth chasing in pitch design unless the pitcher really needs to optimize an eephus (MAYBE!). Knowledge of the gravity effect is really more descriptive than it is actionable.

Magnus shift and spin movement

If you were paying attention earlier, you remember that Magnus shift is caused by the changing path of the ball, and pitches move plenty even without the help of gravity.

In September, Dan Aucoin offered some related notes on the Driveline Baseball blog in his thorough review of all things spin axis. (And for you scarce few trigonometry haters who didn't immediately whip out your calculators earlier, he also provided a nice chart for converting between degrees of gyro spin and spin efficiency. Thank him, not me.)

He compiled data on changes in spin efficiency between release and the front of the plate as measured by a Rapsodo 2.0. His numbers show that glove-side movement tends to increase spin efficiency while arm-side movement tends to decrease spin efficiency. Think about that for a minute. This suggests that, on average, breaking balls could move more as they get closer to the plate while fastballs and changeups could move less.

The above idea gets a little complicated when you consider that we already know that pitches lose velocity as they approach the plate. That has a negative impact on Magnus force, but because the pitch is moving slower, there's more time for the force to affect movement.

Aucoin continues the analysis by stating that the 8%-10% spin efficiency increase on breaking balls equates to only 1"-2" of "late" movement. That certainly isn't much, even if it's late.

Shyamalan!

You just read like 10 paragraphs about Magnus shift and the big conclusion was that it doesn't affect spin movement much at all. That would mean that spin direction and spin efficiency are all you really need to know.

Is that true? Pitching would be pretty boring if it were that easy!

Non-Magnus effects are real. Part II drops soon.


Scouting Grades: Speed

February 20, 2020 • Scouting

Some grades are straight-forward, objective evaluations, but others are quite subjective and open to varying degrees of bias. The Scouting Grades series aims to discuss different tools and how they are evaluated.

Speed is one of the more objective evaluations, but it isn't as straight-forward as one might think. Let's start with a fairly common chart that some of you have probably seen before. This chart contains the generally accepted guidelines for objectively converting a batter's Time to 1B into a scouting grade for speed.

Time to 1B Grades (seconds)
LHB Grade RHB
3.9- 80 4.0-
4.0 70 4.1
4.1 60 4.2
4.2 50 4.3
4.3 40 4.4
4.4 30 4.5
4.5+ 20 4.6+

Grades are typically meant to represent a normal distribution centered around 50 as MLB average (or 5 on a 2-8 scale) where 40 is 1 standard deviation below average and 60 is 1 standard deviation above average. A quick look at the StatCast baserunning sprint speed numbers for 2019 blows that idea out of the water.

128 batters averaged 4.55+ seconds on competitive runs to first base. That's almost exactly 25% of the 510-player sample objectively sitting at or well below the bottom of the scale. The median time of 4.38 seconds is roughly a 35 according to this scale. For comparison, normally distributed speed grades would put 68.2% of players between 40 and 60, with an additional 15.9% above 60, leaving 15.9% below 40, and only 2.1% below 30!

I took a quick crack at dividing the Savant list into separate tabs for left, right, and switch hitters and posted it in a Google Sheets document - 2019 MLB Baserunning Speed. I may have missed a leftie or two (#manualData) as right-handed (the default starting point), but a few lefties sneaking into the righties data won't ruin the samples. Here's what the chart would look like based on the split data with 333 right-handed batters and 132 left-handed batters. (44 switch hitters were left out since their times were presumably mixed.)

2019 MLB - Time to 1B Grades (seconds)
LHB Grade RHB
3.794- 80 3.794-
3.985 70 4.009
4.176 60 4.224
4.367 50 4.439
4.558 40 4.654
4.749 30 4.869
4.940+ 20 5.084+

This chart is a more accurate representation of the actual Time to 1B for MLB players with the one exception being that no one would qualify as an 80 runner.

MLB clubs have undoubtedly been aware of this disconnect since stopwatch times were first compiled on a spreadsheet. An educated assumption here would be that clubs are more or less ignoring current speed grades in favor of objective measures from the player tracking technology deployed across ballparks all over the baseball world. Yet the guidelines remain in effect in most scouting contexts.

Where the scouting element may actually come into play is in projecting future speed. More on that later.

The Before Time / The Long, Long Ago

Before player tracking systems were everywhere, measuring every runner on every play, the only way to get objective speed measurements came from scouts' stopwatches. Time to 1B is a standard because it is a fixed-distance sprint that is run by every batter.

To properly capture a Time to 1B, a scout anticipates contact, attemping to start the stopwatch at the exact moment that bat hits ball, and then reads the batter's steps, attempting to stop the stopwatch at the exact moment the batter's foot touches the base.

As error prone as this might sound, you may be surprised to learn that scouts actually get pretty good at this with practice. Is it as good as a player tracking system? Obviously not. Does it get the job done anyway? Somewhat surprisingly, yes.

Speed elements and application, the downside of relying on Time to 1B

What does Time to 1B really tell you about a player's speed? It doesn't really tell you his peak speed, and it doesn't really tell you how quickly he accelerates either. What it does tell you is a decent approximation of the two.

Take another look at the spreadsheet I prepared. You can get a decent idea of who accelerates well by looking for players that are faster to 1B than their sprint speed peers. For instance, it's pretty interesting to see Jeff McNeil average a 4.10 with average sprint speed.

For Time to 1B, peak speed would need to be significantly faster to make up for below average acceleration, given the relatively short sprint. Peak speed really comes into play over longer sprints: gap fly balls, doubles and other two-base sprints, and especially triples. In other words, Player A might be slower than Player B to 1B but faster than Player B to 2B on a double. Does Time to 1B actually tell you which player is faster?

Speed impacts defense almost purely as it relates to range. Outfield defense typically falls into the same acceleration-and-peak mix as baserunning, but for most infield defense, acceleration is far more important, with peak speed generally only coming into play on pop-ups in No Man's Land.

But there's something else about Time to 1B that you may have not considered yet. Different batters have different swings and require different adjustments to transition from swinging to sprinting. Balance, momentum, stance, and overall effort each affect that batter's ability to recover from the swing and get moving toward 1B, and every batter's Time to 1B has this swing effect rolled into it. 2 players could have the exact same acceleration and peak speed but different Times to 1B because of different swings!

There is no swing effect on defense, and that may be the only thing that really prevents Time to 1B from acting as a near-perfect proxy for an outfielder's defensive range. For infield range, Time to 1B would seem to have little or no correlation. (NOTE: I'd enjoy looking at a study that digs into this idea, and I'll cover range more completely in the Defense entry in this series.)

Projecting Future Speed - A Case Study

This could probably be an entire series of articles by itself, so we're going to floor it for a bit, then slam on the brakes, get out of the car, and do a walk-around.

The one thing to keep in mind is that, absent an alternative guideline, a speed projection should target the player's speed at physical maturity, not the end of the player's career. Physical projection plays an immensely important role in projecting speed.

Nomar Mazara made his Double-A debut with Frisco late in the 2014 season. He was 19 years old and had a wire frame on which you could hang a lot of mass. He showed coordination but lacked any sense of athletic explosiveness. He routinely ran 4.70+ to 1B.

He was reportedly 6' 5" when he signed (source) as a 16-year-old and was now listed at 6' 4", so a scout could fairly assume that Mazara had been that tall for at least 3 years, all while working with professional strength coaches and trainers. By all accounts, he would get stronger and heavier as he got older.

Mazara was a 20 runner with a profile that screamed for a negative speed projection, so of course he returned to Double-A Frisco in 2015 running sub-4.40.

There's a brightside, though. Having jumped two grades in one off-season, there was now room for negative projection! That may sound like a joke, but sticking with the negative projection on the 2015 report is the right call. The better Time to 1B obviously indicates more explosiveness, but everything else in the projection is still true.

If you thought he was going to be a large, lumbering fellow at maturity in your original projection, the only difference in the new projection would be some lighter lumbering.

What else could this two-grade jump indicate? It takes a lot of work to jump a grade in anything, and Mazara jumped two grades in a single off-season! A scout would be crazy to positively project Mazara again, but the jump alone is arguably enough of an indicator that the negative projection should be smaller than originally projected.

Positive speed projections are extremely rare outside of young, undeveloped athletes. In Mazara's case, it seems reasonable to conclude retrospectively that Mazara still fell into that categry, but between 2014 being his third full year as a professional and the rarity of positive projections even within that category, a positive projection would have been met with skepticism.

TL;DR

  • Scouting for speed is probably going the way of the dodo -- if it hasn't already -- thanks to tracking technology that puts a scout's stopwatch to shame, but physical projection is still the scout's domain.
  • A competitive Time to 1B -- measured from bat-on-ball to foot-on-bag -- represents a good-enough estimation of most practical applications of speed in baseball.
  • Projecting speed is the art of projecting physical maturity against present ability.

Still Learning 11 Years Later

February 5, 2020 • News / Announcements

You wouldn't typically expect 11-year-old blog posts to change, but that's exactly what I've done. Two of my earliest blog posts have been updated. I wrote them when I was new both to blogging and to trying to understand what I was writing about. The combination made for awkward language and muddled concepts.

Updating the old posts seemed a far better idea than writing new posts and having to constantly wave my hands at people reading the old ones. At the same time, I do not want to give the impression that the posts as originally written in 2009, so each post contains a note indicating the January 2020 update.

The first post remains one of the most popular posts on the blog -- Biomechanics: Ulnar Collateral Ligament. It was primarily updated for clarity but also includes an expanded conclusion to address a logical oversight.

The second article was a long-winded description of the relationship between internal rotation and elbow extension in a typical arm action -- Delayed Internal Rotation: Performance Implications. It was also updated for clarity by simplifying the language used to discuss the topic and by removing some irrelevant material.

In addition to these updates, I have planned this as something of a relaunch of the blog. I will write occasionally on a variety of topics generally in the realm of player development and scouting. I don't advise you to expect a regular publishing schedule, but new stuff will definitely squeak out as my rather ambitious personal schedule permits it.


Is it really supported by science?

February 8, 2017 • Research Review

On its surface, this question isn't all that hard to answer. The typical internal translation is often, "Is there a published research paper that supports this?" While that's a very common thought, there are a few problems with it.

Problem #1: Confirmation bias.

So there's a paper with an affirmative conclusion. Is it the only paper on that subject? Are there papers with a negative conclusion?

Confirmation bias and cherry-picking can allow someone to paint a fairly abstract illustration of what research really has to say on a subject. Confirmation bias seeks out only affirmative research, while cherry-picking is intentional disregard of research that doesn't affirm your assertion. Both methods of research review fail to appropriately consider the entire body of research.

This does not mean that every single research paper on a subject must be read in order for a reader to have an opinion on the subject. In many cases, this is actually quite an onerous task. In my opinion, it is generally sufficient to include discussion of both affirmative and negative research.

Problem #2: You may be reading a lie.

Some people are not smart enough to understand what they've read. Some people don't even read the research papers that they cite. Some people are so disingenuous with their manipulation of the research that it is equivalent to a bald-faced lie.

A once prominent pitching voice* frequently claims that his hypothesis is supported by science; however, the paper he cites in his defense actually contains conclusions that neither support nor refute his hypothesis. The comment to which he often refers is actually just a hunch offered by the paper's primary author. Even the primary author mentions that the research does not support it!

The only way to parse through claims like this one is to read the research for yourself, especially when investigating a potential coach.

* This is vague on purpose. I am not trying to start a flame war here.

Problem #3: Non-specific conclusions, poorly worded abstracts.

I recently read a 21-year-old research paper for the first time. What caught my attention was the conclusion in the abstract that explicitly stated, "This finding suggests that the muscles on the medial side of the elbow do not supplant the role of the medial collateral ligament during the fastball pitch."

After digging into the paper, it's clear that this conclusion is not generally applicable as its language would suggest. The full text of the study states that every member of the test (injured) group had pain when they threw.

In other words, there were no asymptomatic injured pitchers, and since pain inhibits performance it is impossible to know which element was to blame for the measured differences: the structurally compromised UCL or the pain.

Everything about the study was fine except for the wording in the abstract. Because the abstract completely skips over the fact that the entire injured group actively felt pain, it's impossible to know without reading the full text that the abstract's conclusion was specific rather than general.

It would have been 100% accurate with only 4 extra words, "This finding suggests that the muscles on the medial side of the elbow do not supplant the role of the medial collateral ligament during the fastball pitch in injured, symptomatic pitchers." Those 4 words pack a lot of meaning into the conclusion.

Wrap-up

One of the tougher issues that I think a lot of people have with research papers is understanding exactly what they're reading. Frequently, people only have access to a paper's abstract, and as described above, that can be pretty misleading.

Maybe it's just delusions of grandeur on my part, but I'm planning a research review series that will aim to dig into the guts of some published research on pitching, throwing, and arm health. Features will include study design, discussion topics (some papers have extremely interesting discussion sections), and conclusion analyses. Look for it in the coming weeks.