Do Better Pitchers Actually Have Better Command?

Command and control. They sound like terms we’d use during a military operation. But no, these are two skills that are very important in baseball. The two refer to the same general ability to throw pitches in the best locations for the pitcher. There is a distinction between the two. As I understand it, control represents the pitcher’s skill in throwing strikes; command refers to the pitcher’s ability to throw pitches where he intends to throw them.

We can’t actually measure command. That would require knowing where the pitcher wants to throw the ball, and we don’t know that unless he’s telling us before each pitch. CommandF/X  — Sportsvision’s technology that tracks the catcher’s glove — would help, but that’s not publicly available.  What we can do, though, is measure pitch location through PITCHf/x. This should work as a good proxy.

We know that command is very important, and that the best pitchers, on the aggregate, display much better command than lesser pitchers.

Or do we?

I was curious as to what makes the best pitchers in the league better than everyone else. Is it command, raw stuff or deception? We can probably say with a great deal of certainty that some sort of combination of these components creates the disparity between good pitchers and everyone else. But it’s hard to say how much each component contributes. In this post I will look at the difference in command — if a difference exists — between the best pitchers in the league and everyone else.

I defined the best pitchers as those who were in the top 25% percentile of FIP. Everyone else falls below that mark. Before dissecting the data, the two groups look pretty similar:

 

This graph is actually made from a random sample of pitches from each group, because my computer wasn’t so keen on running a density estimate for 700,000 pitches. 

The graph is from the catcher’s perspective, and the dotted box represents the strike zone. The two graphs look very similar, so there’s not a lot we can learn from visual inspection. In addition, there are various biases that we have yet to address.

We know that better pitchers have a different distribution of counts than other pitchers; the elite hurlers are in 0-1, 0-2 and other pitcher-friendly counts much more often than lesser pitchers. This is important for the command discussion because the pitcher’s target is largely dictated by the count. In a 3-0 count, the pitcher wants to throw a strike. But in an 0-2 count, throwing a strike is much less important. If we break up our command analysis by count, pitcher handedness and batter handedness, we again find that the two groups perform very similarly. Here I restricted my sample to only look at fastballs (of any type):

 

The graph is very tiny, so make sure to click on it to enlarge. It shows the horizontal pitch location in every combination of handedness and count. The lines are the horizontal borders of the strike zone, and the left side in each graph is inside to a right-handed batter. For left-handed pitcher to left-handed batter matchups, the sample gets a little small in 3-0 and 3-1 counts. Other than that, though, there are plenty of pitches with which to work.

This graph was frustrating for me. As fans, we often hear preaching about how “you will get beaten if you throw the ball down the middle.” These words are repeated by everyone. It’s as if it’s a law nature — a truth as ubiquitous as gravity itself. But do the best pitchers really avoid the middle of the plate more than the others?

It’s true that we don’t know everything about context. We haven’t looked at the batters to whom these pitches were thrown, the ballpark in which the pitches were thrown, the umpire behind the plate or how previous pitches worked against the batter. But over the course of the season — in hundreds of thousands of pitches — you would think that these variables even out.

With vertical pitch location, it’s more or less the same story:

It looks like the best left-handers are throwing up in the zone a little more often that than the other lefties, but there’s not much else that jumps out.

But of course, these aren’t the only ways to measure command. Say we narrow down our samples to only starters. We’ve been told that the heart of the plate is the end of the world for pitchers. This means the best pitchers should be hitting the borders of the zone more often. I looked at the horizontal location of all pitches to see if they were within half a foot of the horizontal edge of the strike zone, adjusted for batter handedness. I found the percentage of pitches that fit this criteria, and then I split up the results by count:

 

Here, we do see a small, but noticeable, difference. In all counts where the pitcher is ahead, top pitchers had a higher percentage of being close to the border of the zone than other pitchers. But this is not a trend we see in all counts: When in 2-0, 2-1, 3-1 or 3-2 counts, the best pitchers actually threw fewer pitches close to the zone’s border. This seems intuitive. When ahead, it’s best to try and hit the edge of the zone. But when behind in the count, it’s best to throw the pitch in the heart of the zone to get a strike. I ran a test of significance for the difference in proportions for pitches on 0-2 counts, and I found a significant difference at a 95% level. I have not tested the other differences for statistical significance, but we should be pretty comfortable with our analysis knowing that each count contains many thousands of pitches.

The magnitude of the difference seems pretty small. Over the course of a full season — say we have two pitchers — each who threw 3,000 pitches. One is a top pitcher; the other is not. In 0-2 counts, top pitchers throw 52.5% border pitches, while other pitchers throw 51%. About 6% of all pitches come in 0-2 counts, so let’s say that each pitcher has 180 pitches in  0-2 counts, ignoring the fact that the better pitcher will surely have more of these situations. We would expect the top pitcher to throw 94.5 border pitchers, and the other pitcher would throw 91.8 border pitches. That’s really not much of a difference. Over the course of a full season, the difference in border pitches is probably fewer than 20 pitches — on average — between top pitchers and everyone else.

To make sure that this method was reasonable, I calculated the percentage of close border pitches for each pitcher, and I then found the relationship between that and walk rate. The relationship is very significant and in the right direction (more border pitches means a lower walk rate), but the R-squared is very low at 4%. Despite the low explanatory power, I’m satisfied that this metric measures what we think it does. As another sanity check, I arranged the pitchers in descending order from highest percentage of border pitches to lowest. The leader was Mariano Rivera at 58%.

As suggested by Jeff Zimmerman, I also looked at how often these pitchers were throwing first-pitch strikes. Looking only at starters and pitches that were not put into play, top pitchers threw 57% first-pitch strikes and other pitchers threw first-pitch strikes 54% of the time. Even though the difference looks small, it’s actually a pretty significant spread when looked at over an entire season. About 23% of all pitches are both thrown in the first pitch of an atbat and are not put into play. Returning to our mythical pitchers from before, each pitcher is throwing about 690 pitches in this situation. This means that the top pitcher is going to throw about 393 first-pitch strikes, while the worse pitcher is going to throw 372 first-pitch strikes. That’s about 21 at bats where the top pitcher is starting off in a better situation.

Bias, Bias, Bias

Better pitchers are supposed to have better command. And it seems that they do, but by a small margin. But better pitchers also have better stuff (which will be addressed in a later post). If a pitcher has bad stuff, they almost have to command the ball well to pitch in the majors. Using this logic, we should observe an inverse relationship between stuff and command. As a crude measure of stuff, I found the average fastball velocities for each pitcher. If the hypothesis is correct, we should see an inverse relationship between velocity and the percentage of border pitches. And that’s exactly what we found. Albeit with a low level of explanatory power, there is a statistically significant inverse relationship between the percentage of border pitches and velocity.

This means that everything we’ve looked at so far has underestimated the difference between top pitchers and everyone else. But by how much?

I accounted for stuff by restricting the sample to only pitchers who had fastball velocities between 90 mph and 93 mph. Velocity is a crude proxy for stuff, but it seems accurate enough for our purposes. When we only look at starters in this velocity range, we find a larger difference in the percentage of border pitches:

 

I grouped types of counts together to make the graph a little easier on the eyes. Counts where there were more strikes than balls are “ahead,” and counts where there were more balls than strikes are “behind.” Counts where the two were equal are “neutral.” These differences are larger than before, but by a small number.

Putting it all together

Before I got into PITCHf/x analysis, I always assumed that command would be obvious with data. I wasn’t naive. There’s an incredible amount of anecdotal evidence supporting the notion that better pitchers have better command. And according to the data, this does seem to be true — just with a much smaller magnitude of difference than expected. If we could re-run this analysis with minor-league pitchers, I’m sure we’d find a much larger difference because there’s a massive selection bias when looking at major-league pitchers. If there’s only a small difference in command, then we should see significant differences when looking at raw stuff and deception.

Or at least, that’s what we would expect.

References and Resources

*PITCHf/x data from MLBAM via Darrel Zimmerman’s pbp2 database. Scripts by Joseph Adler, Mike Fast and Darrel Zimmerman

*Mike Fast’s strikezone definitions



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Just Jim
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Just Jim
4 years 6 months ago

I love the articles at fangraphs, but this one made my brain hurt……………

NJ_Andy
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NJ_Andy
4 years 6 months ago

I have nothing constructive to add, I simply want to say, “Well done, Mr. Weinstock.” This was tremendously interesting AND informative. I can’t wait to see the continuation of the series.

You have begun to reshape my entire view of pitching.

Yirmiyahu
Member
4 years 6 months ago

Very interesting. There’s a few ways that a good pitcher can get into pitcher’s counts without necessarily relying on ‘command’. Swinging strikes that aren’t necessarily in the zone; called strikes that are not swung at because they’re so nasty; umpires giving the pitcher the benefit of the doubt.

Paul
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Paul
4 years 6 months ago

When you separate the “better” pitchers by using FIP, aren’t you dropping out a lot of guys who have a large ERA-FIP spread due to their weaker peripherals, i.e., “command pitchers”?

Antonio bananas
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Antonio bananas
4 years 6 months ago

very good point. FIP is such a flawed stat because strikes, balls, and home runs are every bit as luck driven as a dribbler up a middle. Short fences, wind blowing out, etc. Why not just use the top 10 WAR guys on this site and the top 10 on B-R?

Antonio bananas
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Antonio bananas
4 years 6 months ago

or top 25 % when you split the difference between the WAR here and B-R? It just seems that FIP is would be incredibly bias towards strikeout pitchers, which isn’t what you’re looking at here with command necessarily.

SpaldingBalls
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SpaldingBalls
4 years 6 months ago

You really don’t understand DIPs theory, do you?

Paul
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Paul
4 years 6 months ago

Spalding: The point is FIP is already regressed. I am actually surprised that this analysis showed any difference at all. Why would you use a regressed statistic to study a fundamentally raw performance variable?

Joel
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Joel
4 years 6 months ago

Good, detailed analysis. Thanks for sharing.

Liam
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Liam
4 years 6 months ago

I think it would’ve been interesting to approach this from the opposite side of the research. What advantages can very good command bring to a pitcher?

Ratwar
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Ratwar
4 years 6 months ago

Honestly, I think this article falls into the old saying, “there’s more than one way to skin a cat.” A top pitcher should have at least one outstanding ability, and it is possible to be a top pitcher without good control, if you have great stuff.

What I would do is split the sample more, and make the bins smaller. As you mention, the bins are currently so large that you don’t bother running them. They’re currently too big to get a good feel for what they represent.

thomas
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thomas
4 years 6 months ago

command f/x will tell us the answer to this question

PiratesBreak500
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PiratesBreak500
4 years 6 months ago

So question- Right now, better pitchers tend to have better stuff. They also tend to be more accurate, at least on the first pitch. If better pitchers tend to have better stuff (thus have less control), wouldn’t that weigh downward on the first strike percentage? So isn’t the fact that the better pitchers throw first pitch strikes more often even more impressive (even if it’s only about 21 at bats per year)?

Cliff
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Cliff
4 years 6 months ago

So, you think there could be “control”, the ability to throw strikes, but not “command”, the ability to throw pitches where you want them to go? That seems like a logical impossibility to me.

walt526
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walt526
4 years 6 months ago

It’s logically inconsistent with respect to a “straight” pitch (e.g., a fastball) since location and velocity are the primary determinants of its effectiveness. But for other types of pitches, movement is as important as location and velocity. For example, consider a slider that the pitcher intends for it to break sharply out of the strikezone as it approaches the plate. Should the slider fail to break (i.e., a “hanging slider”), it will stay in the zone and will be a relatively easy-to-hit for the batter. On the one hand, since it remains in the strikezone, one might say that the pitcher has exerted good control; on the other hand, since it didn’t do what the pitcher intended it to do, one might also say that the pitcher had poor command of the pitch.

That is, for pitchers whose arsenal is mostly throwing pitches that vary in location and velocity, then essentially control=command. But for pitchers who rely on movement of their pitches, it seems clear to me that control and command are two interrelated, but definitely distinct, properties.

Bip
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Member
Bip
4 years 6 months ago

To me that begs the question of what’s the point of even mentioning control. It’s not a positive thing to throw a pitch into the zone when you don’t want to, so measuring control would seemingly reward pitchers for leaving breaking pitches over the plate and punish them for successfully breaking them down out of the zone. Command, however, weeds these out and gets to the heart of what we actually want to measure.

walt526
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walt526
4 years 6 months ago

While I agree that command is the more important variable, as Josh noted in his article, we generally cannot directly observe command because we don’t know what the pitcher intended to do with every pitch. All we get is some noisy measures that allow us to extrapolate whether the pitcher has good command.

For example, if a catcher sets up low-and-away and the pitch almost hits the batter in the head, then we can conclude that the pitcher failed to exercise good command of that pitch. But, at least historically (BIS might be collecting those data now, I’m not sure), data has not been collected on where a catcher sets up versus where the pitch goes. Since command and control are highly correlated, we can make some valid inferences regarding command based on measures of control. For example, the historical data that we do have are things like BB, HBP, WP, etc. In more recent years, we have pitch location data, but those are also measurements of control not command.

And so, at least as I understood the methodology, Josh analyzes command based on the pitch location data set that only has measures of control. At the beginning, he stipulates that control is not a perfect proxy for command, but then conducts his analysis under the assumption that measures of control are informative of command given the assumption of high correlation between command and control.

baty
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baty
4 years 6 months ago

I am forever confused and torn with the loose definitions of words like “stuff”, “control”, “command”, etc…

I would argue that the “control” objective of a pitcher could be to locate strikes as far from the zone center as possible… Also, pitchers might be targeting a general direction within the strike zone under the assumption that the “command” of his stuff will locate the pitch in an area with reasonable success… the degree of control and command depends on who’s being thrown to, when of the pitch is being thrown, and the type of pitch that’s being used.

Here’s the progression I typically see:
A. the pitcher type
B. the batter type the pitcher is throwing to
C. the time in which the pitch is being thrown (pitch situation)
D. the type of pitch being thrown (pitch selection)
E. the target locations within a pitch selection (pitch control)
F. the nature of a pitch through its targeted zone location (pitch command)

Cool article…

sc2gg
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4 years 6 months ago

I bet if you remove Kyle Drabek from the “Everyone Else” category, they’d be even with the Top Pitchers.

FrankTheFunkasaurusRex
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FrankTheFunkasaurusRex
4 years 6 months ago

I bet if you remove Roy Halladay from the “Top Pitchers” category, they’d be even with everyone else

Donovan McNabb
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Donovan McNabb
4 years 6 months ago

“throwing up in the zone”

I’ve got a copyright on the phrase “throwing up in the red zone”, so watch yourself lest you want a call from my lawyers.

Bob Ray
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Bob Ray
4 years 6 months ago

This is mind blowing… Impressive.

Jon L.
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Jon L.
4 years 6 months ago

This is a long article, so I’m setting it aside to read with care, but I did have one initial reaction. I would be more interested to see the top 25% of pitchers compared to the next 25%, or the middle 50%. By comparing them against the bottom 75%, you’re confounding what sets apart the best pitchers with what sets apart the worst pitchers, since the bottom 25% are certain to have worse stuff and worse control and worse stamina and worse everything else (if you consider the group mean) than the top 25%. This may dilute the most meaningful comparisons.

Paul Berthelot
Member
Paul Berthelot
4 years 6 months ago

great article, really informative must have taken a long time to complile/analyze all the data, excellet job

delv
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delv
4 years 6 months ago

I’m definitely interested in seeing more that takes velocities into account. You only mentioned the 90-93 mph subset; why is that? I figure that the 93-96 subset and the 87-90 would be more revealing.

And what was the minimum IP/pitches thrown to be included in your data set?

Also, why FIP and not xFIP or SIERA? I’m sure part of the benefit of pitching on the corners is weak contact. And why did you drop out pitches that were put in play? You really touched on a lot of information and variables, but there’s also a good bit that obfuscated by your presentation.

Great stuff, Josh. Looking forward to the book!

Chris from Bothell
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Chris from Bothell
4 years 6 months ago

Excellent work.

Do you anticipate that looking at the bottom of the pile will generate somewhat inverse results? E.g. that those in the worst 25% would throw less pitches close to the zone’s border when in hitters’ counts, due to being too fine and missing outside, throwing curves that don’t curve, etc.? Or are bad pitchers bad for a variety of reasons, but good pitchers will all tend to have the sort of traits and pitch patterns you’re outlining here?

jimbo
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jimbo
4 years 6 months ago

Looking at all counts as equal might be masking the command differences. Is it possible to run your logic using wpa instead of just count? My guess is the top 25% will separate more in high leverage situations.

Keith_Allen
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Keith_Allen
4 years 6 months ago

I’ve done similar work over the past 3 years and even invented a Command Stat that I call Pre-FIP. IMO, Command is basically a precursor to FIP. Like one person said, there are many ways to skin a cat. Getting into pitchers counts and avoiding hitters counts is one of them. With this stat, you’ll find that Zach Grienke’s command is just average, and that he gets into a lot of hitter’s counts. It kind of explains why his ERA is usually higher than his FIP.

TK
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TK
4 years 6 months ago

I really like this article. Though I thoroughly disagree with you about how you defined control and command, I really like how you went about looking at command as you defined it.

Honestly, wouldn’t you think with all the factors that go into pitching, one single factor, the ability to throw border pitches, would not be that different between top pitchers and other MLB pitchers? Because there are so many factors, such as deception, stuff, consistancy of motion, and decision-making, one factor is unlikely to make a huge difference when looking at all pitchers as a whole or in large groups.

I’m sure if you look at it the other way – does superior command help you pitch better – you’d find that it clearly does. If that isn’t the case, I’d be truly shocked.

Mike Bravard
Guest
4 years 6 months ago

Great Article. Thank you!
I have a son pitching at the D2 level. Watching his development over the years has made me a want to be student of the pitching skill set. Your article was enlightening. My son has never had much “stuff” as defined by velocity but has always been relatively difficult to hit. Deception is not considered in your article I suppose, because it is even more difficult to measure than command. That does not lessen its importance.
Command, deception and movement take a back seat to velocity in scouting circles with good reason. The eventual first round picks always score relatively high on the velocity scale. Most baseball people believe the the other skills can be taught. I am convinced that every pitcher has a “velocity ceiling” but also the same is true for command and deception.
I’d be interested to learn your take on deception. In my view it is the combination of three factors; 1. hiding the ball 2. shortening the distance to the plate 3. having a different delivery than is the norm.
Comments?

siggian
Guest
siggian
4 years 6 months ago

Re: Deception

I think another factor in deception is the ability to throw an unexpected pitch. If you are able to throw a good change-up when the batter is thinking fastball, you’re likely to get a good result. Pitch sequencing is only part of that. The pitcher needs to command the pitch enough to get the batter to either swing at the ball or give up on it when he shouldn’t.

channelclemente
Guest
4 years 6 months ago

My pure speculation is that by looking at pitching to target, the catchers glove as a target, you swallow the elements of accuracy and sequencing in one parameter.

JB Knox
Guest
4 years 6 months ago

Deception doesn’t necessarily come from tricks such as hiding the ball or a different delivery or even shortening the distance to the plate. For instance many pitching coaches teach that a a shorter stride helps with breaking stuff, thus taking the distance shortening part of the equation out of the mix for those pitchers.

The greatest form of deception is and always will be throwing all of your pitches with the same arm angle and arm speed while changing spped and movement. The best way for your son to do this is by adding more friction to the ball or experimenting with his grips. But I wouldn’t suggest tinkering with his wind-up or mechanics to get deception into the fold.

I pitched and played SS in D3 and had some tryouts back in the early 90s. As a hitter I can tell you that the most deceptive pitches I ever saw came when the pitchers 1) Used the same arm speed and motion on off-speed pitches as they did with their fastball 2) Pitching backwards. Pitching backwards is the art of throwing off-speed in fastball counts such as 2-0 change-ups and such.

As a hitter I can tell you that regardless of the delivery you will always pick up the ball. If a hitter (well-trained one at least) sees fingers or before he sees the white/red of the ball, we know that is breaking stuff or off-speed. If I see all white I am sitting dead-red fastball.

Mike Bravard
Guest
4 years 6 months ago

Thanks to Siggian and Knox for their comments.
I agree that pitch sequencing and throwing all your pitches from the same angle are essential. As you point out this may be the most obvious factor in deceiving the hitter. Certainly it is the most common to most pitchers who have similar deliveries and pitch repertoires. The game, however, has changed radically over the last 20 years as coaching has become far more standardized. Both hitter’s and pitcher’ approaches look more alike than different.
This, I think is an opportunity for some pitchers to experiment with different look.
I do not believe Knox’ assertion that the delivery has no impact. If that were true there would not be so many right handed side arm specialists (the number of these guys is increasing on major league rosters). There are subtle differences in how the pitch is perceived by the batter. Chris Young and Doug Fister are two examples of pitchers who have high strike out rates with average velocity.
The ability of Luis Tiant and Pedro Martinez to drop down in certain situations was very effective.
The LH/RH statistical splits are due in part because of the differences in delivery of the ball from both sides of the rubber. Tony LaRussa once experimented with the idea of having 6-8 semi-starters who would pitch 2-3 innings every 3 days and thereby show a different look almost every time the lineup turned over.( I believe the strategy would work well in hitter’s parks like Coors, and especially in the NL when you could take advantage of the early pitching changes with tactical PH opportunities.)
In my son’s case his ability to fool hitters with his all legs and arms delivery and good command has kept him moving up the ladder despite being a late bloomer physically.
Now that he is filling out his long armed 6’4” frame, he may do better than just climb the ladder.
Thanks again for the comments!

Sheriff Stathead
Guest
4 years 6 months ago

It’s interesting to see the differences were minimal in the graphs. But then i think of how baseball is more of a game of inches than yards. So it makes sense. Great article.

cuck
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cuck
4 years 6 months ago

It looks to me like in the pitch density picture, that top pitchers throw lower pitches in general.

Jimbo
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Jimbo
4 years 6 months ago

Agreed.

Hitters make worse contact when looking at the top of the ball, so getting it into the zone (control) is step one. To become top-25% you have to keep it down in the zone (command).

Jackson NOLA
Guest
Jackson NOLA
4 years 6 months ago

Since you had to limit Stuff to velocity, thus ignoring movement, it could be that an accounting for the minimal difference between top pitchers and the also rans would have to assume Part Movement, and Part Mistakes to MLB Hitters tend to go 400 feet. Like the writer, I would assume that the best make fewer mistakes, thus accounting for some of the difference.

I think we know that guys who can throw in the mid nineties get many chances in the show, but those who can’t, don’t. We hear all the time from tv color guys that “an MLB batter will hit a straight fastball, even at 95, if he expects it.” To me that implies that a velocity limited sample is going to include a disproportionate percentage of stuffless monkeys, who can throw high heat, but without movement. Furthermore, placement around the plate is much less effective for a guy without movement. And that would go a long way toward explaining why the best pitchers do so much well than the bottom 75% — it’s MOVEMENT, which we can’t run the numbers on at this time.

TheBigsdisciple
Member
TheBigsdisciple
4 years 6 months ago

Could there possibly be a manufactured difference between top pitchers and “everyone else” because of conventional wisdom, especially in the “Bias,Bias,Bias” section of the article.

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