Long before Moneyball came along, the game of baseball embraced numbers and statistical analysis. Every single team in baseball has a stats department. The ways and means have certainly changed, but the goal remains the same: use numbers to find a competitive advantage.
These days sophisticated tracking systems like PitchFX and Statcast record pretty much everything that happens on the field: how much a pitch moves, how quickly an outfielder takes his first step, how hard a catcher throws down to second base on a stolen base attempt. You name it, and there’s a number for it.
. There are, surprisingly, many outside vendors involved. This nugget from Anderson’s piece stood out to me:
“Right now, we have teams out there, who, when they evaluate a player, they’re taking their 2017 schedule, they are prototyping the opposing pitcher array -- perhaps, if they’re really sophisticated, even assuming what the seventh, eighth, and ninth innings look like against those teams -- and they’re simulating a batter’s performance, a prospective acquisition, his performance against that pitching opposition, in those ballparks,” Gennaro said. “Because they’re not looking at his stats, they’re looking at his exit velocity and his launch angle.
“If you hit the ball 86 mph to let’s call it straight-away right field at Yankee Stadium at a 32-degree launch angle, depending on the wind, that probably drops into the first couple of rows. If you hit that same velocity and launch angle at AT&T Park, Hunter Pence is taking two steps in to field it. So, all of those things are being incorporated into the analytics of the most sophisticated teams.”
That’s wild. Teams are essentially modeling an entire season using all the available data to get an idea how a player may perform for them. These are still human beings of course, so nothing is 100 percent predictive, but if you have the data available, why wouldn’t you use it to try to forecast performance?
The days of targeting players with high on-base percentages because the the rest of the league is undervaluing them are long, long gone. Now teams are using information in more complex ways to gain an advantage. One possible method: using state of the art pitching machines to mimic opposing pitchers. Seriously, it’s possible.
Before each series -- and often before individual games -- coaching staffs will huddle up with their players to examine the opposing pitching staff. They’ll watch video and read scouting reports. That’s been going on for years. All that scary data is put into an easy-to-digest format for players. Communication is crucial.
Now, that said, you can watch as much video and read as many scouting reports as you want. Nothing can replicate the on-field experience. Knowing Dodgers ace Clayton Kershaw has a killer curveball and likes to throw it in two-strike counts is one thing. Trying to hit it is another. Video and scouting reports only help so much.
These days clubs can go beyond video work and scouting reports. State-of-the-art pitching machines make it possible to model specific pitches like, say, Kershaw’s curveball. Driveline Baseball, a data-driven training facility frequented by many big leaguers, used data to replicate Indians righty Carlos Carrasco’s changeup with a pitching machine last year:
In this example the pitching machine replicates the spin rate of Carrasco’s changeup, as well as the angle, the release point, the whole nine. It comes out of the pitching machine like it comes out of Carrasco’s hand.
It goes without saying modern pitching machines can be a powerful tool. Rather than prepare for a game by hacking away at soft tosses during batting practice, players can get an idea of what it’ll be like to face that day’s opposing starter in the batting cage with a fine-tuned pitching machine. This is taking video work and scouting reports to the next level.