What We All Saw in the Playoffs

Usually these posts follow some kind of narrative structure. You wouldn’t necessarily say you come to FanGraphs for the storytelling, but any decent article is supposed to tell a story, even if it’s mostly statistical. I’m not going to bother this time. I’m not going to lead in with some manner of gripping anecdote. I just want to show you all a bunch of postseason numbers. I want to show them to you, because some of them are interesting, and postseason numbers aren’t always the easiest things to track down. Certainly not if you want to compare them to the same year’s regular-season numbers. That’s why I’m here today.

I’ve shown some of these plots in the past. What’s different now is that I have a few more plots, and also that the 2018 postseason is officially complete. Below, eight images, and limited commentary. How has playoff baseball compared to regular-season baseball over the years? I’ve gathered a whole host of statistical indicators, mostly with the help of Baseball Reference. Join me, if you will, on a quick analytical journey. We always guess at how the playoffs might play out, or which trends we might observe. We don’t have to guess about what’s already in the books.

I’ve examined the wild-card era, stretching back to 1995. And there’s something important to note, here: The playoffs don’t necessarily feature a representative sample of major-league baseball teams. Playoff teams are all better teams, with better players, and they might have their own characteristics. It would be better to compare all these playoff numbers to weighted regular-season numbers for only the teams that made the playoffs, but I’ve settled here for simplicity. It’s just something to keep in mind as we proceed. Shall we proceed? I don’t know where to begin, so let’s start with the most dramatic-looking plot. For the regular season and for the playoffs, here are the rates of innings thrown by the starting pitchers:

Even if you didn’t know the actual numbers, this is something I imagine you could feel. The regular-season decline is continuing, and this year it was accelerated by the Rays’ adoption of the opener. But the Rays didn’t make the playoffs. Other teams made the playoffs. In the regular season, 60% of all innings were thrown by the starters. In the playoffs, 50% of all innings were thrown by the starters. That is, of course, the low, with the bullpen sharing the load equally. I think this is a trend that can only go so far, but there’s nothing magic about 50%. This could conceivably drop even lower still.

Note that that factors in only each game’s two starters, and it doesn’t account for starting pitchers who throw out of the bullpen, like we saw from Chris Sale, or David Price, or Nathan Eovaldi, or so on. That’s a whole other trend. And a much more difficult one to calculate!

So, related to the above, here’s what’s happened in terms of pitchers used per nine innings:

Historically, in the playoffs, compared to the regular season, we’ve seen an increase here of 10%. This October, we saw an increase of 20%, or to put it another way, we saw the playoff number jump by half of a point. Half of a pitcher! Relative to the 2017 playoffs, that is. Last October, teams used 4.7 pitchers per nine. This past regular season, teams used 4.4 pitchers per nine. This October, teams used 5.2 pitchers per nine. When the starters aren’t working so deep, the bullpen has to pick up the slack. It’s all easily and obviously connected.

Where might you see one consequence of this? Game length:

There’s nothing new about this. The average nine-inning playoff game has lasted half an hour longer than the average nine-inning regular-season game. This year, the gap was 40 minutes, instead of 30. The gap rose by five minutes over last year, even though this time around, playoff offense went down. There are a number of contributing factors here. More pitching changes. Longer commercial breaks. Widespread sign-stealing paranoia! Batters and pitchers simply working slower. Deeper counts. I don’t really like to complain about playoff pace, because the playoffs are important and I’m not as invested as an actual fan of one of the competing teams. But, boy, the playoff pace can really drag, and it’s only part the fault of TV.

What else can we look at? There’s always concern that playoff strikeouts go through the roof. Not so much:

Obviously, the playoff strikeout rate is almost always higher than the regular-season strikeout rate. The pitchers are better, and, while the hitters are also better, the pitchers are more better, relatively speaking. And they throw harder. But at least nothing here is particularly out of control. Historically, the playoff strikeout rate has been higher than the season rate by 12%. This year, the difference was 11%. The playoff strikeout rate didn’t increase at all from 2017, even though the regular-season numbers jumped. That’s promising. Right? I think that’s promising.

Here’s something I like. In some circles, it’s referred to as the Guillen Number. Here are the percentages of runs scored on homers:

Last year was nuts. Last year set a regular-season record for homers, and then in the playoffs, homers accounted for more than half of all run-scoring. This time around, things looked a lot more normal. The regular-season numbers calmed down, and then in the playoffs, the rate settled at 42%. Over this window, the so-called Guillen Number has increased by 9% in the playoffs. For 2018, the increase was just 5%. These playoffs weren’t about dingers; these playoffs were about the Red Sox driving everybody in with two outs for some reason.

I should get to runs. Here are runs:

There was a bit of a slip this October, as the playoffs teams collectively dropped below four runs per nine innings. Historically, in the playoffs, run-scoring has dropped by 11%. This year, in the playoffs, run-scoring dropped by 14%. It follows that, when run-scoring is down, OPS also goes down:

We just saw a collective playoff OPS of .659. For the sake of reference, I don’t know why I’m thinking about Freddy Galvis, but this year Freddy Galvis ran an OPS of .680. Mike Zunino ran an OPS of .669. Historically, in the playoffs, OPS has dropped by 6%. This year, in the playoffs, OPS dropped by 9%. I’ve already mentioned how starters are throwing less and less, meaning relievers are throwing more and more. You can understand why the playoff hitting environment might be increasingly hostile. But for the final image, I want to share a factor that’s easy to overlook. Let’s consider the matter of BABIP:

You might not intuitively think that playoff BABIP would decline. But it declines, and it declines by a lot, even though, again, the playoffs select for better teams, which select for better hitters. Historically, in the playoffs, BABIP has been lower by 6%. This year, in the playoffs, BABIP was lower by 9%. The past two years have been the first years in the wild-card era to have a playoff BABIP under .270. It’s harder to get batted balls to find the ground. It’s harder for a number of reasons.

The pitching is better. The pitchers, individually, mostly throw faster, on account of playoff adrenaline. The defenses are presumably better, and the playoffs afford teams a greater ability to scout their opponents. Temperatures go down! That’s another thing that might kill some fly balls. Playing around with some Statcast data for 2015-2018, the league-average regular-season expected wOBA has been .314. In the playoffs, it’s been .307. But the league-average regular-season actual wOBA has been .317. In the playoffs, it’s been .292. Batters aren’t hitting the ball dramatically worse; they’re just ending up with dramatically worse results. That’s been the pattern, and that’s what happened in 2018.

That’s all I’ve got. Thanks to those of you who stuck around. We’ll do it all again a year from now, I’m sure. This isn’t the last that you’ve seen of this data.

Jeff made Lookout Landing a thing, but he does not still write there about the Mariners. He does write here, sometimes about the Mariners, but usually not.

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Dieter Von Wolfhausen
3 years ago

very cool. i’ve been wondering about this kind of thing for a while… thanks for doing this!

Smiling Politely
3 years ago

Agreed! Would love to see the next steps, some of which you alluded to (starters used as relievers, impact of the shift, pitches per pitcher per game/series, etc.) and see if there are any other analytic gems!