Agreed - I should have said “… predicted before they are released”.
Yes, but the ability to disguise this - so the batter can’t tell from the release what pitch is coming - is a big asset to a pitcher.
Is there a way to confirm that 2,500 RPM figure? That’s about 42 revolutions per second, and it’s hard for me to believe that a pitcher can possibly make it spin that quickly.
Edit: I read that “average” pitcher spin is still 2,200 RPM. I’m pretty surprised at that.
2500 RPM works out to a tangential velocity (speed of the spinning ball at it’s surface) of about 22 mph. Considering that the translational velocity is up to 100 mph for a fastball, it seems feasible to impart that much spin to it as well.
A fastball takes about .4 s to reach home plate. At 42 rps, that’s 16 revs from hand to glove. That seams (:D) about right.
The announcer said Chad Green’s pitch was almost 2,500 RPMs. 2,400 something. I rounded it up to 2,500.
He continued to say that Green ranked #5 in RPMs. So, there are other pitchers with more spin.
You’re probably right, but people can certainly throw a whiffle ball that rises. Put enough backspin on a whiffle ball and it rises as it moves forward. You can do the same even easier with a beach ball. I suppose at some revolution RPM, you could get a baseball to do the same. Just guessing, as I don’t know how to go about calculating that given a baseball’s weight and diameter.
But, yes, whether it actually rises or just doesn’t fall to earth at the expected speed, a fastball with lots of backspin will be higher than a batter expects it to be when it crosses the plate.
By quite a remarkable amount, in fact. “Vertical movement” on an MLB fastball - which means how much it doesn’t drop, as compared to a ball with no stitches thrown exactly the same - can be upwards of a foot. No kidding.
The spin rates became a big thing in the past year or two, part of the Statcast suite of seemingly interesting but ultimately meaningless numbers.
Basically, the more the spin, the more a ball curves. Instead of saying, “Seth Lugo has a great curveball,” they say “Seth Lugo’s curveball is measured at 3498 rpm.” It tells nothing that isn’t obvious to a trained observer of the game, but puts a number on it to prove they can put a number on it.
But it does tell something. Suppose you have two pitchers, both of whom have great curveballs. But which one is greater? You only have the budget to sign one; which one do you pick? If you can put a number on it, then you can pick the higher number.
Well, not necessarily. There can (and should be) a slew of other factors: how does the ball curve (not all curves are created equal, regardless of spin rate. Angle of spin matters. The type of delivery matters). Also, endurance, consistency, pitch arsenal, etc.) It’d be foolish to base a signing decision on just that number. I personally really wouldn’t care about those number. I would care about the numbers like how do real-life athletes perform against that pitcher. Maybe the high rpm pitcher telegraphs his pitch better than the slightly lower rpm pitcher, so batters read it more often. Maybe the slightly lower rpm pitcher has a slight sideward break to the curve that makes it trickier to hit than a 12-6 curve (or vice versa).
The one who can vary it, and throw another pitch or two for strikes too. A guy who always throws the same thing will eventually get hammered, as batters adjust to it.
I meant, assuming all else is equal. And even when all else isn’t equal, what teams actually do these days is construct elaborate statistical models of all of these numbers, and their interactions, to determine what they mean for win rates, and then hire the pitcher who’s most likely to win (or, who will have the biggest impact on win rate per cost). You need numbers to run statistical models.