It's been four months since I published the first entry in the Scouting Grades series, and it's fair to say that motivation to continue blogging about baseball has been limited in that time. With the 2020 draft in the rearview, I found myself thinking about scouting grades again.

If you haven't already, it's probably a good time to review the post on Speed. Now, let's talk about POWER.

Power wins games. Power puts butts in seats. No other tool has a showcase -- the home run derby -- that exists specifically to elevate and celebrate a specific tool. It should come as no surprise that power also draws big signing bonuses and buys prospects more time to develop.

In this context, development most often means translating raw power into game power, the actual production of runs. That development generally takes the form of increased plate discipline which is not limited to swinging at fewer balls but also includes learning and taking advantage of pitch locations that really allow the hitter to get to that power.

Raw Power vs Game Power

Before player- and ball-tracking technology, raw power grades were determined by watching a hitter unload on baseballs -- usually during batting practice, a scout's best opportunity to see a lot of swings in a short amount of time. Raw power was essentially how hard a player could hit the ball, frequently evidenced by distance.

[Note: batting practice is not the only input, obviously. Game swings matter more and commonly result in harder contact than batting practice swings. However, scouts will almost always see fewer game swings than BP swings, and plenty of hitters will show you what they've got during BP.]

The Raw Power Scouting Scale (roughly):

• 20 – Even with a favorable gale force wind, the ball probably isn't going over the fence.
• 30 – A stiff breeze should do it.
• 40 – Doesn't need help, but you don't know it's over the fence until it is.
• 50 – Hey, there's some pop!
• 60 – Stadium vendors and people on the concourse should pay attention.
• 70 – The ball hits weird parts of the stadium, and occasionally leaves to check out other places.
• 80 – The ball has a greater than zero chance of escaping Earth's atmosphere.

Game power is an assessment of how often a player is going to tap into that raw power against MLB pitching. There's no escaping the subjectivity required for a game power grade since it relies on, among other things, the player's future hit tool and future raw power which are both projected by the scout.

This produces an unbelievably wide spectrum of projections and results. There are guys you've never even heard of with top shelf, 80-grade raw power that projected to hit approximately 0.000 at the highest level. Then you've got freaks like Frank Thomas and Miguel Cabrera that are just as likely to win a big league batting title as they are to win a homerun crown.

The Game Power Scouting Scale (roughly, thrown into disarray by the new baseball; not funny):

• 20 – 5 homeruns in a single season would be incredible.
• 30 – ~5 homeruns per season.
• 40 – ~11 homeruns per season.
• 50 – ~18 homeruns per season.
• 60 – ~26 homeruns per season.
• 70 – ~35 homeruns per season.
• 80 – Homerun crown contender.

Of the obvious variables that limit raw power in games -- pitch recognition, plate discipline, swing length, and others which will be discussed in the Hitting post -- there is one in particular that can limit a hitter with plus hitting and plus raw power to mediocre or even below average production: launch angle.

Exit Velocity & Launch Angle

Three names immediately jump to mind when I think about how a low launch angle stifles power: Nick Markakis, Eric Hosmer, and Yandy Diaz. That's three big dudes with big raw power, decent batting averages, and just not very many homeruns. Depending on your age, you may recall that, as prospects, Markakis and Hosmer were fairly widely believed to be potential perennial 40-homerun hitters. Diaz, who arrived just in time for launch angle to become a hot button issue, has been frequently noted as a guy that hits the ball as hard as anyone else in the game.

Last season, all three were in the Top 50 in Hard Hit % (95+ MPH) -- Hosmer #32, Diaz #43, Markakis #48 -- just ahead of Mike Trout (#49) and Fernando Tatis, Jr (#50).

Last Season, all three were in the Top 60 in Average Exit Velocity -- Diaz #20, Markakis #30, Hosmer #57 -- ahead of Anthony Rendon (#64). Trout checked in at #51. (Stats according to StatCast via Baseball Savant.)

In 469 plate appearances, Markakis hit 9 homeruns. In 667 plate appearances, Hosmer hit 22 homeruns. In 347 plate appearances, Diaz hit 14 homeruns. That's 45 homeruns in just under 1,500 plate appearances.

In 600 plate appearances, Trout hit... 45 homeruns.

Given 2.5x the number of plate appearances, three hitters that are ostensibly better at hitting the ball hard than Mike Trout combined to produce the exact same number of homeruns as Mike Trout alone.

The key difference (and admittedly not the only difference) is launch angle.

Eric Homser had a 2.1° average launch angle. Yandy Diaz had a 5.7° average launch angle. Nick Markakis had a 7.3° average launch angle.

The average launch angle for all MLB batted balls was 11.2°.

Mike Trout had a 22.2° average launch angle.

The point of all of this is to illustrate that translating raw power into game power requires hitting the ball in the air. A player can hit 100 MPH ground balls all day, but it won't result in power production.

Context and Projection

As scouting evolves thanks to the ever expanding use of technology, the scout's role will increasingly be to provide context for objective data rather than authoring almost entirely subjective reports. With the proliferation of Trackman, HitTrax, and similar systems, for example, it's a matter of course to have objective data for a player's exit velocity and launch angle. A scout provides little of use by assigning a 20-80 grade for present raw power.

A player's future raw power, on the other hand, is a contextual grade usually backed by an assessment of physical projection. Physical projection offers insight into a player's potential through continued growth and added speed/strength. An 18-year-old that could still grow a couple of inches and has never lifted a day in his life could get a 2-grade bump, while a 23-year-old with a mature build generally gets none.

When it comes to game power, the hit tool is the big separator. It is easily the most complex tool grade and is frequently broken into several sub-grades, and the realization of hitting potential often relies on additional external factors that are not easy for a scout to assess. That really is a topic for a future post, but a few quick examples will illustrate the type of context scouts should be chasing.

The path of the barrel, including its overall length and depth, plays a key role for both power and hitting. While a long, flat path might lead to a lot of overall contact, it isn't likely to lead to much hard contact. A shorter path on plane with the pitch has a better chance of producing hard contact, and being on plane with the pitch has the added benefit of an increased launch angle.

The length of the swing ties into timing which has downstream effects on pitch recognition and plate discipline. All other things equal, a hitter with a longer path to contact has to start to swing earlier, giving the hitter less time to see the ball before launching a swing. Less time to see the ball means worse recognition which will lead to bad swings and bad takes.

When timing is more easily disrupted, the contact point "moves" to different parts of the swing. Generally speaking, if the swing is late, the ball is more likely to be popped up because the point of contact has "moved" deeper where the barrel hasn't come back up to the anticipated point of contact yet. If the swing is early -- particularly on slower pitches that drop more -- the ball is more likely to be hit on the ground because the point of contact has "moved" out front where the barrel has already risen past the anticipated point of contact.

These issues are amplified more in swings that are further from the plane of the pitch.

Projecting a future game power grade can seem a lot like witchcraft, but it boils down to just a couple of questions:

• Will the player's raw power increase or decrease?
• How will the player hit against top-level pitching?
• Will the player hit the ball in the air?

At this point, projecting a player falls into the gap between scouting and player development. Amateur scouts can get to know a guy well enough to have a good idea of the player's development potential ahead of the draft, but the same can't be always be said for pro scouts who are watching another ball club's players. This development gap is a complex topic and will hopefully be the focus of a future post.

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.

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.

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.)

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.