While looking through Tampa Bay's 2021 position player stats, six players stood out as exceptional values. Randy Arozarena, Brandon Lowe, Joey Wendle, Mike Zunino, Wander Franco, and Willy Adames each produced in excess of 3.5 bWAR with a salary under $3 million.

Using that as a baseline for the rest of the league, I found that there were only 27 such Elite Value position players for the 2021 season. The Rays' six put them at the top, and the only other team with as many as three was the Cardinals. 13 teams didn't even have one Elite Value position player.

[Note: Willy Adames is counted for both Tampa Bay and Milwaukee (not shown). While he, specifically, was markedly more valuable for Milwaukee, counting him and similar players on both teams is sufficient for this article.]

Over the past 10 full seasons, only 14 out of 300 teams had at least 3 Elite Value position players. The 2018 Dodgers had 4 and are the only other team with more than 3: Cody Bellinger, Max Muncy, Kiké Hernández, and Chris Taylor.

Expanding the criteria to explore its arbitrary nature, I also looked at position players that produced at least 2 bWAR with a salary below $4 million. Of the 71 such High Value position players in 2021, the Rays had 9. The next closest team, again, was the Cardinals with 5.

Over the past ten years, a team has had at least six High Value position players just six times, and a whopping four of them were the Rays. The only team to exceed six such players was -- surprise! -- the 2021 Rays with nine.

By either measure, the Rays 2021 season was very special in terms of position player value. How were these Elite Value players acquired?

Randy Arozarena (2020)

Randy Arozarena loudly introduced himself during the 2020 MLB Playoffs when he seemingly came out of nowhere to hit 10 home runs in 20 games with a ridiculous 1.273 OPS. The Rays acquired Arozarena ahead of the 2020 season from the Cardinals along with Jose Martinez and a draft pick in exchange for Matt Liberatore, Edgardo Rodriguez, and a draft pick. Arozarena wasn't able to maintain that insane homerun pace in 2021, but he was named the American League Rookie of the Year.

Brandon Lowe (2015)

Lowe is the only player on this list that was drafted by the Rays. A third-round pick in 2015 (87th overall) out of the University of Maryland, Lowe has comfortably exceeded expectations. Of the 1,215 players drafted in 2015, only Alex Bregman (2nd overall), Andrew Benintendi (7th overall), Walker Buehler (24th Overall), and Paul DeJong (131st overall) have more career bWAR so far.

Joey Wendle (2017)

The Rays acquired Wendle in 2017 for a player to be named later (Jonah Heim). The following season, he broke out with 4.9 WAR, tying for 21st in MLB! After a lackluster 2019, Wendle was an Elite Value again in 2020 and 2021. This offseason he was traded to Miami for Kameron Misner (2019 1st round pick).

Mike Zunino (2019)

In 2019 the Rays traded Mallex Smith and Jake Fraley to the Mariners for Mike Zunino, Guillermo Heredia, and Michael Plassmeyer. In his first 2 years with the Rays, Zunino struggled offensively and had a combined -0.3 bWAR. Following the 2020 season, the Rays re-signed him for $2 million (with a club option for 2022) and were rewarded with a 3.8 WAR season, the 3rd most for a catcher in 2021.

Wander Franco (2017)

You won't see Wander Franco’s name on this list again after he signed an 11-year, $182 million contract. He originally signed as an international free agent as a 16-year old. Consistently atop prospects lists since he signed, Franco has the potential to be one of the best players in the game. He played in just 70 games during his rookie season, but his 3.5 WAR in less than half a season is nothing short of remarkable. Only seven hitters in 2021 had a lower strikeout rate (min 300 PA’s), and of those seven, only Yuli Gurriel had a higher OPS+.

Willy Adames (2014)

Before Franco took over at shortstop, the position was manned by Willy Adames. The Rays acquired Adames along with Drew Smyly in the 2014 David Price trade. Adames was having a good season in low-A but entered the year ranked 30th on Baseball America's Tigers top 30 prospects list. A 2018 rookie, Adames had his first Elite Value season in 2019 and was on-pace for another in the shortened 2020 season. His production declined in 2021 before he was traded to Milwaukee, where his production sky-rocketed to 3.5 WAR in only 99 games.

These six players were acquired in different ways across seven seasons. Lowe (draft) and Franco (international free agent) are home-grown talents, while Arozarena, Wendle, Zunino, and Adames were all acquired via trade.

With a committment to competing at a high level despite historically low player payrolls, it's important for the Rays organization to find all-star production from inexpensive players. Having this many in a single season suggests quite a bit of luck, but the Rays' historical success with Elite Value production shows there is more to it than just luck.

It's been a while since Part IV in this series, and since that time, I realized that I had been holding all of the information I needed to make a case that spin deception is a thing. The theory, most simply put, goes like this:

Wake effects deceive the batter by creating unanticipated movement.

The long-winded version is bit of a walk, but it's an easy one. Professional hitters have really good vision. Like, crazy good. They also have reps upon reps upon reps against live pitches. The result is that they are exceptionally adept at seeing and reacting to spin. Given the time hitters have to react to pitches at the professional level, it's practically a reflex. When a pitch moves differently than this reflex expects, the pitch is harder to hit.

Identifying Wake Effects

Since MLB switched over to the Hawk-Eye system, pitch tracking data has been elevated in a way that helps us identify this effect. The old "spin direction" measurement was really movement direction all along. With Hawk-Eye reporting directly on the pitch's actual spin direction, we can now fairly easily compare these two numbers.

Movement direction is no longer directly reported, so we have to dust off those old trigonometry functions and do some MLB-specific adjustments to get movement direction on the same scale as spin direction. Luckily, most coding languages and SQL have a handy atan2(y, x) function that does a lot of the heavy lifting. (I will answer emails and tweets about this math, but I won't further extend this lengthy post by elaborating on trigonometry.)

Once we have spin direction and movement direction, we can very easily figure out how far apart they are. The catch is that you can't assume a whole lot from such comparisons, and here's why.

A specific difference -- spin direction minus movement direction for a specific pair of values -- means something different for different tilts. An easy example is that a +30° difference for a pitch with a 180° spin direction (12:00 tilt) means it had a 150° movement direction (11:00 tilt), but for a pitch with a 0° spin direction (6:00 tilt), a +30° difference means it has a 330° movement direction (5:00 tilt). At first glance that's going to seem perfectly logical to you, but the first pitch moves to the right (batter's perspective) more than expected and the second pitch moves more to the left than expected!

A further wrinkle is found on sliders, tight curveballs, and any other pitch that finds itself in a gyro cluster near 0 vertical movement and 0 horizontal movement. Pitches with high gyroscopic spin are extremely sensitive to small variations in spin direction (tilt). This leads to exaggerated differences between the two direction angles. You set your sample data to exclude certain pitch classes, but that merely reduces the geometry problem instead of accounting for it. So...

Let's factor in movement distance. There are two "clear" approaches to this. You can be completely serious, like Glenn Healey and Lequan Wang, and use physics to reasonably calculate the side force, or you can be like me and use a somewhat reasonable alternative that assumes equal movement at both angles and measures the difference between the two endpoints. Healey and Wang definitely have the more accurate mathmatical approach, but while they are asking, "How much did side force affect this pitch?", I am asking a less specific question: How far did this pitch wind up from where the batter expected it to wind up? (The difference in approaches results in my values being smaller than Healey and Wang.)

I decided to express the directions as Spin Tilt and Movement Tilt since "tilt" is well understood and widely used. I settled on the name Tilt Difference for the difference between them and Deception Distance for the final value. But that's not all...

I did a truly excessive amount of thought before I touched any numbers, and decided that I also wanted to look at the absolute value of these differences. It didn't seem right to me that a pitch that generally has either +2" or -2" Deception Distance should average to a near-zero value because in reality there is an average 2" difference! This value gives us a second way to look for hidden value. We can check not only the average Deception Distance, but also the average Absolute Deception Distance.

Free Data!

I published a spreadsheet with all of this data: Spin Deception Data. It's a pretty neat little toy that lets you use the Data -> Filter views selection to shuffle between pitcher handedness and pitch type. The dataset is the complete pitch type summary set for 2020 as reported by the public MLB StatsApi. The filters are limited to pitchers that threw at least 20 of the filtered pitch type. Some dependent variables included in the sheet are swinging strike rate, foul rate, and in-play rate broken down by batter handedness as well as overall exit velocity and launch angle.

The second sheet in that document contains scatter plots with trend lines. Here are the most intriguing results, which I'm sure greatly please @NotRealCertain. The first set of charts is sinkers thrown by RHP.

RHP Sinkers

Those are some pretty strong trendlines suggesting a positive relationship between both versions of Deception Distance and how poorly a ball is hit, and we see them again with the LHP sinkers. The fun thing about the LHP sinkers charts is that the trendlines are in the opposite direction because LHP sinkers have "positive" Tilt Differences.

LHP Sinkers

Further research

I'm not an analyst, and I just do this for fun, so this is about as far as I want to take things myself. I'm sure there's plenty more to dig into, but it will have to be one of you that does it. If you have questions or comments, feel free to reach out to @texasleaguers on Twitter or use my contact form to send me an email.

Feel free to download, copy, and reuse the data in the spreadsheet, but please credit me, the blog, or the website if you publish any analysis related to the data contained therein.

Part I in this series covered the basics of the Magnus effect and how pitch spin creates movement. Part II covered some interesting research being done by Barton Smith to explain non-Magnus seam effects.

At his blog, baseballaero.com, Smith has logged research results as he's worked through several experiments aimed at analyzing and describing a baseball's aerodynamic wake as it relates to the position of the baseball's seams. As the posts stacked up and more impactful conclusions could be drawn, he realized he needed a way to describe seam orientation.

A few emails later, he and I had worked out the basics of a simple system, and a couple of days after that, we co-authored the first post about describing seam orientation.

Based on a few subsequent conversations and work done to produce visualizations, we realized that describing seam orientation wasn't the only missing piece needed to completely describe a pitch's spin.

In this post, I'm going to discuss the system as it is currently implemented by the pitch spin modeler. (You may want to have that open in another tab while you continue reading.)

A preview of the modeler, for those that don't care to click the link above.

Describing spin basics

There are already three extremely common and well understood components of spin description. There is no reason to mess with them really.

"Spin rate" is a simple measure of how fast the pitch is spinning, typically in rotations per minute (RPM) though you may see a different unit of measure in a math-heavy analytics post or article.

"Tilt" is the two-dimensional representation of the direction of the Magnus effect created by the spin. For example, a fastball with pure backspin has a tilt of 12:00 because the force created by the Magnus effect points straight up which is 12:00 on a clock face.

This clock-face-based description was popularized by Rapsodo and widely welcomed as a solution to the rather constant confusion that resulted from trying to communicate spin axis as an angle. (Astute readers will notice that, while tilt doesn't directly describe the spin axis, it does do so indirectly via the right-hand rule.)

"Spin efficiency" is commonly used to represent the percentage of spin that contributes to the Magnus effect. A lower efficiency means there is more gyro spin. A less common term for this is "Active Spin", though it is still represented as a percentage. In the pitch spin modeler, I have labeled it "Active Spin" under the Efficiency header.

UPDATE (4/16/2020): To more accurately reflect the role of gyro spin in pitch movement, the "Efficiency" header has been renamed "Magnus Efficiency", and the "Active Spin" slider has been converted to "Gyro Angle" with the efficiency percentage following in parentheses.

Improving the basics: gyro spin is missing something

On the pitch spin modeler you'll see another setting under Efficiency called "Gyro Pole". This setting indicates which of the two spin axis poles is "responsible" for the efficiency percentage. Technically speaking, both spin axis poles are equally responsible since one can't move without the other, but for now "responsible" means that the particular pole is forward on the leading surface of the ball.

Generally speaking, RHPs will have a "negative" gyro angle, and LHPs will have a "positive" angle. So... Why not establish a positive pole and a negative pole? Why not just use positive and negative angles? My short answer is this: for something that sounds so simple, it is rather confusing and non-descriptive when it comes to practicality.

Take, for example, a curveball with 6:00 tilt thrown by a RHP with 80% spin efficiency thanks to a gyro angle of 36.9°. Should that angle be positive or negative? What if a LHP threw it? Take another example: a fastball with pure side spin. If the bottom pole is forward, is that positive or negative? Is the answer to that question the same for both a RHP and a LHP?

Identifying the specific pole on the same clock face as the tilt is easy and perfectly descriptive. The two poles will always be at +3 hours and -3 hours, respectively, from the pitch's tilt. The pitch modeler already identifies them for you, so you simply select which pole should be angled forward!

12:00 Tilt with 77.1% Active Spin at opposing poles. Left: 9:00. Right: 3:00.

Back to seam orientation

This one was a little tricky. The clock face was already taken, and this really can't be solved by a two-dimensional model anyway. The general baseball audience probably doesn't understand Euler angles or quaternions. (I barely do, and I coded a pitch spin modeler that depends on them!)

As far as I could determine -- with the help of Barton Smith and Tom Tango -- there were really only two options for eloquently describing seam orientation: (1) a coordinate system that uses latitude and longitude like a globe and (2) a pair of angles that tell you how to turn the ball.

The coordinate system has its advantages. It's well known. It's fairly commonly understood in general terms. It's precise, and it's specific. It also has some important disadvantages. Though it's fairly commonly understood in general terms, I'd venture to say that players and coaches don't have a lot of practical experience using it every day. What would an orientation of (34, -117) actually mean even if they could find that spot on the ball?

So I decided to push forward with what seems like the simplest possible approach: rotate the ball from the top, rotate the ball from the front. Both rotations, for descriptive purposes, are clockwise for positive and counter-clockwise for negative.

Orientation redundancy and pitch grips

Due to the pattern of the seams on the baseball, there are a lot of different ways to grip the baseball to create identical spins. For example, from the origin position, a 180° Top rotation gives you a different look but produces the same spin as the 0° origin! Likewise, -90° and +90° both produce a standard four-seam spin.

Two different orientations that produce the same spin. Left: -90° Top rotation. Right: +90° Top rotation.

The original release of the pitch spin modeler restricted Top rotation to a range of -90° to +90° to avoid confusion regarding unique spin models, but I quickly felt that it unnecessarily prevented useful visualization of two-seam grips that use vertical seams.

With it extended to a full 180° in both directions, you can use the tool to model any grip you can think of!

Altogether now

The pitch spin modeler has 6 variable inputs that are used to completely describe a baseball's spin. That is twice as many as were widely used just a few weeks ago. Take any one of those 6 inputs away, and you create a blind spot in the pitch description.

With all 6 given, it becomes a matter of math to determine where movement-critical seams are located. Once the math is ready, this will fantastically complicate both the standard constant acceleration model and the more advanced Nathan model for pitch movement that do not currently account for seam-based wake effects.

The next entry in this series will discuss currently available tracking technologies and what they can and can't tell you about a pitch. (Don't hold your breath, though. It's going to take some time because there will be a lot to verify ahead of posting. There will probably be several unrelated posts between now and then.)

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.

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.

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.

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.

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.

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.