Familiarity and Framing, Investigated

Something that makes total sense is that catchers need to know their pitchers. Catchers, after all, are the guys calling all of the pitches, and catching many of the pitches, and you often hear about guys who either are or are not on the same page. It makes sense how familiarity could have an effect on pitch-calling. It also makes sense how familiarity could have an effect on pitch-receiving, as greater familiarity will yield a greater understanding of how pitches move and where they’re likely to go.

Earlier this very Monday, Eno posted an article titled “Familiarity Breeds Better Framing“. Eno was passing along material he got in speaking with Oakland catcher Stephen Vogt, and Vogt used Luke Gregerson as an example of a guy he doesn’t know well enough yet. Vogt needs to learn Gregerson’s tendencies and movement in order to maximize his own ability to catch him. This all got me wondering: can we see anything in the PITCHf/x data? What do the framing numbers look like for pitchers who’ve changed teams?

The familiarity I’m talking about is the familiarity between a pitcher and a catcher. I’m going to use changed teams as a proxy for changed catchers, since most pitchers don’t have an R.A. Dickey/Josh Thole thing going on. You’re most accustomed to seeing framing data broken down by catcher, since it’s the catchers who’re doing the actual framing, but you can also see the same numbers by pitcher. That’s what this study focuses on. The expectation is that pitchers that change teams end up with worse framing numbers, because then they’re throwing to new catchers.

I looked at this in two ways. First, I looked at pitchers who changed teams midseason. Then, I looked at pitchers who changed teams between seasons. Out of convenience, I elected to use a different methodology for each. For the former, I used data pulled from StatCorner. For the latter, I did some calculations using data pulled from FanGraphs leaderboards. Both methodologies have agreed well with one another in the past, in different studies, so I was comfortable with this approach.

First, the guys who changed teams midseason. During the PITCHf/x era, there have been 36 pitchers who threw at least 50 innings for two different teams in the same season. StatCorner keeps track of a couple of stats — balls called within the usual umpire strike zone, and strikes called outside of the usual umpire strike zone. Here are the average numbers for those pitchers before and after getting moved:

First team: 16% balls on called pitches in zone
Second team: 16%

First team: 7.8% strikes on called pitches out of zone
Second team: 7.9%

Absolutely nothing there. Now for the guys who changed teams between seasons. For this analysis, I used my own metric that I put together a while ago. Using FanGraphs plate-discipline data, you can calculate expected strikes. Then you can look at the difference between expected strikes and actual strikes, and the numbers you get out of these calculations agree well with the more rigorous pitch-by-pitch analyses. I calculated something called Diff/200 — the difference between actual strikes and expected strikes, above or below average, per 200 innings. I examined the six-year PITCHf/x era.

I looked for guys who threw at least 50 innings in consecutive years. I then excluded the guys who were traded during one or both of those seasons, to make the data cleaner. I was left with a sample of 921 season-pairs. Of those, 164 featured pitchers who changed teams over the winter. The remaining 757 featured pitchers who stayed on the same team. Here’s how the numbers compare:

Year 1, pitchers who changed: -2.1 Diff/200
Year 1, pitchers who stayed: 0.8

Year 2, pitchers who changed: -0.7 Diff/200
Year 2, pitchers who stayed: 2.4

Difference, pitchers who changed: +1.4 Diff/200
Difference, pitchers who stayed: +1.6

If I wanted, I could analyze the little patterns in these numbers. The pitchers on new teams regressed toward average, but were still a little worse than the pitchers who stuck around. However, consider the scale. We’re talking about one, two, three strikes per 200 innings. So, a small fraction of one run, which is hardly worth talking about. If you squint, you can see a familiarity effect. If you squint any harder, your eyes will be closed and you’ll see nothing but darkness. There just isn’t anything here that screams “I’M SIGNIFICANT!”

Intuitively, you’d think, when a pitcher changes teams, he’ll get received a little worse, because the catchers don’t know him. I couldn’t really find anything with pitchers who changed teams in the middle of the year. I couldn’t really find anything with pitchers who changed teams between two years. And the more I think about it, the more I think this is the result I should’ve expected. A result of nothing meaningful.

For one thing, most catchers have been catchers for a while, and while catchers, they’ve had to catch a lot of different pitchers. Catchers in the majors are selected for meeting at least some kind of bare-minimum threshold of adequacy, so it stands to reason they’re quick learners. They basically have to be. They have to learn pitchers quickly, and they have to learn hitters quickly, or else they probably won’t be very good catchers. I don’t doubt that a new pitcher takes a little getting used to. It might just be the getting used to takes very little time at all.

And for another thing, how different are most pitchers, really? How different are their pitch types? The catcher knows what pitch is coming, because the catcher called for it. Most fastballs move similarly. Most changeups move similarly. Most pitchers tend to miss in similar ways. Luke Gregerson throws a bunch of different sliders, but he’s unusual in that regard. He might take a little extra getting used to. It’s presumably still a quick process. Pitchers and catchers are in constant communication, and catchers seem able to learn pitchers in a hurry.

For purposes, at least, of receiving. Familiarity might have a bigger effect on game-calling, and therefore on results. It could take longer for a catcher to figure out a pitcher’s real strengths and weaknesses in different situations. But as far as just pitches and movements? Plenty of reasons to think it’s a process. Plenty of reasons to think it doesn’t take long.