The Throwbacks Among Us

I imagine you already know that big-league hitters in 2018 strike out an awful lot more than big-league hitters in 2008 did. You could probably guess, too, that they hit for a somewhat lower average and a little less power. Even though some of that power differential will even out as the weather heats up this summer — we’re not exactly comparing apples to apples, here — I think it’s a relatively uncontroversial opinion to say that the game has changed in the past decade:

MLB Hitters, 2008 and 2018
Year BB% K% ISO BABIP AVG OBP SLG
2008 8.7% 17.5% 0.152 0.300 0.264 0.333 0.416
2018 8.8% 22.5% 0.160 0.293 0.245 0.317 0.405
2018 stats through games played 5/27/18.

Furthermore, those changes in the way the game is played have forced us to adjust our understanding of what good, bad, and decent performances look like. We have had to reconcile ourselves to the notion that, although just 20 qualified hitters struck out more than 22.5% of the time in 2008, 50 are above that mark right now, and another 40 or so finished above it last year in a full season’s worth of data. Striking out nearly a quarter of the time doesn’t make a hitter an outlier anymore, and we’ve had to adjust our internal expectations for player performance accordingly.

And yet there are still players out there whose profiles look basically like the league’s performance overall from 2008 — players, in other words, who walk around the league-average rate for 2018 but strike out a little bit less than it, and hit for a somewhat lower average than we might expect from the average player these days. “Throwbacks” is a word you might use for these people. Xander Bogaerts, for example, has generated an offensive profile over his past 365 days (which I’m using as the basis for this and all subsequent comparisons because 2018 stats alone are still a little fresh) that looks remarkably similar to what we saw from the league as a whole just a decade ago:

Xander Bogaerts vs. 2008
Comparison BB% K% ISO BABIP AVG OBP SLG
MLB 2008 8.7% 17.5% 0.152 0.300 0.264 0.333 0.416
Xander Bogaerts 8.1% 19.6% 0.157 0.299 0.256 0.323 0.413
Bogaerts’ stats between 5/27/17 and 5/27/18.

This particular comparison, upon which I happened almost entirely by chance, got me thinking: which other contemporary players are throwbacks — guys whose offensive profiles appear a little out of place in today’s game but look just about bog standard for another era? Bogaerts is one of them, but who are the others? Which players are the throwbacks among us, playing a version of the eternal game perhaps most at home in the past?

Well, there are many different ways to do this, depending on your goals and desired level of sophistication, but one simple way is to take each of the statistics above and sum the absolute value of the degree to which each contemporary player’s performance differs from league performance in the year we’re interested in. Players with relatively low scores on this measure would be more similar to the target year’s figures, and those with high scores more different.

Using Bogaerts as an example, we might sum 0.069 for his walk rate (0.087 – 0.081 = 0.006; 0.006 / 0.087 = 0.069), 0.120 for his strikeout rate (0.175 – 0.196 = -0.021; -0.021 / 0.175 = -0.120), and so on down the line to get a total difference score of 0.293 (which we can then multiply by 100 to make it look less like a rate stat). This, as it turns out, is the lowest score among any of the 454 players who’ve had at least 100 PA in the past year.

2008 Throwbacks
Name BB% K% ISO BABIP AVG OBP SLG DiffSc
MLB 2008 8.7% 17.5% 0.152 0.300 0.264 0.333 0.416
Xander Bogaerts 8.1% 19.6% 0.157 0.299 0.256 0.323 0.413 29.3
Miguel Cabrera 10.1% 19.3% 0.153 0.298 0.259 0.335 0.412 31.2
David Peralta 8.3% 18.4% 0.153 0.323 0.280 0.346 0.433 32.1
Jordy Mercer 7.3% 17.2% 0.162 0.292 0.258 0.316 0.420 35.4
Jefry Marte 8.8% 19.3% 0.155 0.282 0.243 0.316 0.398 36.8
Player stats between 5/27/17 and 5/27/18.

Now, this isn’t a particularly sophisticated measure of similarity, and it misses out on a lot of things about which we might care were we to have data on them from the last 50 years (for example, fly-ball rate), but it finds enough similar-looking profiles to be interesting and also has the advantage of being extremely simple to calculate. That works for me for an exercise in idle curiosity on a free website, but I suppose you can be the judge.

There are a few notes before we proceed to other years. First, because we’re trying to find players whose lines look like the league’s overall performance in a given year, we’re never going to find players who have done incredibly well or incredibly poorly over the past year. There will be no Mike Trout in this article, and no Chris Davis, either. We will, as you’ll soon see, find players whose poor performance this year looks good in comparison to previous years, but that variation is all within a relatively narrow band of mediocre to somewhat above-average performance. This is not an exercise in extremes.

Second, a word on semantics: because of the unequal distribution of playing time across the league (good players get more playing time than bad players, usually), you are more likely to land on a below-average player in a random sample of all big-league players than you are to land on an above-average one. The comparison figures we’re talking about here, for each decade preceding 2018, aren’t really the figures of a particular “league-average” player in any given year; they’re just the average line for all players in the league in that year — which is rather a different thing.

With all of that in mind, we’ve got a metric, so let’s use it for each of the decades of the past 50 years. Here’s the table for 1998, the year of the home-run race and Monica Lewinsky:

1998 Throwbacks
Name BB% K% ISO BABIP AVG OBP SLG DiffSc
MLB 1998 8.7% 16.9% 0.154 0.300 0.266 0.335 0.420
David Peralta 8.3% 18.4% 0.153 0.323 0.280 0.346 0.433 33.4
Robinson Cano 8.5% 13.6% 0.156 0.298 0.277 0.345 0.433 34.0
Xander Bogaerts 8.1% 19.6% 0.157 0.299 0.256 0.323 0.413 34.2
Jordy Mercer 7.3% 17.2% 0.162 0.292 0.258 0.316 0.420 34.4
Miguel Cabrera 10.1% 19.3% 0.153 0.298 0.259 0.335 0.412 36.1
Player stats between 5/27/17 and 5/27/18.

It turns out that the league’s overall performance from 1998 is a pretty hard profile to find these days. Peralta just doesn’t feel like as strong a fit at the top of the list as Bogaerts did for 2008 — his triple-slash line is too high and he doesn’t quite strike out at the same rate as the average player of two decades ago did — and the list doesn’t get much better from there. If you squint, you can see the similarities between the players listed and the comparison year — these guys certainly look more like an average player of the 90s than, say, Aaron Judge does — but, to some extent, nobody out there really fits the bill, which I think is interesting in its own right. Those old Beanie Babies may be lying around your basement, but the players they watched flit across the screen have almost all left the game. Let’s move a decade further into the past:

1988 Throwbacks
Name BB% K% ISO BABIP AVG OBP SLG DiffSc
MLB 1988 8.1% 14.7% 0.123 0.282 0.254 0.318 0.378
Isiah Kiner-Falefa 7.9% 15.2% 0.119 0.299 0.259 0.331 0.378 21.2
Victor Martinez 8.4% 13.2% 0.124 0.267 0.250 0.317 0.374 23.0
Kolten Wong 8.5% 15.6% 0.119 0.286 0.249 0.337 0.368 26.3
Jason Heyward 8.7% 12.7% 0.119 0.273 0.250 0.319 0.369 31.7
Jarrod Dyson 7.6% 14.4% 0.107 0.281 0.248 0.310 0.354 32.8
Player stats between 5/27/17 and 5/27/18.

Now we’re getting somewhere. In 1988, players as a group struck out a lot less than players do today, just like they did in 1998, but they also hit for much less power than they would a decade later, which opens up room for comparison to a group of players not present on the first two lists. Gone are the players like Cano, Bogaerts, and Peralta, who can occasionally run into one, and on it are a set of players who really haven’t hit for that much power recently (including Martinez, who you may be surprised to find slugged just .372 last season). These players, to a man, look a lot more similar to the 1988 figures than any of the 1998 comps looked to that years’ numbers. It turns out you can still look like a 1988 throwback and get some plate appearances in today’s game, though I concede that prior to running this exercise, I had very little idea who Isiah Kiner-Falefa was. Perhaps the second coming of Steve Winwood. Let’s move on.

1978 Throwbacks
Name BB% K% ISO BABIP AVG OBP SLG DiffSc
MLB 1978 8.5% 12.6% 0.121 0.280 0.258 0.323 0.379
Jason Heyward 8.7% 12.7% 0.119 0.273 0.250 0.319 0.369 14.3
Victor Martinez 8.4% 13.2% 0.124 0.267 0.250 0.317 0.374 19.3
Miguel Rojas 8.0% 10.9% 0.118 0.286 0.267 0.341 0.386 34.9
Kolten Wong 8.5% 15.6% 0.119 0.286 0.249 0.337 0.368 38.3
Isiah Kiner-Falefa 7.9% 15.2% 0.119 0.299 0.259 0.331 0.378 39.3
Player stats between 5/27/17 and 5/27/18.

Ah, this is fun. Turns out that Jason Heyward — who wasn’t quite a perfect fit for the 1988 comparison — looks pretty darn identical to the average player from 1978. Low power, low BABIP, slightly more strikeouts than walks… you name it, and you’ll probably find that Heyward has it (unless, of course, you’re looking for a repeat of his performance from 2012 to -15, in which case please phone Theo Epstein). Unfortunately for Heyward, the rest of the game has moved on in the four decades since the Bee Gees topped the Billboard charts: that 1978 average line you see up there was good for a 97 wRC+; Heyward’s is 83. In baseball and on mens’ upper lips, 70s throwbacks just won’t cut it.

1968 Throwbacks
Name BB% K% ISO BABIP AVG OBP SLG DiffSc
MLB 1968 7.6% 15.8% 0.104 0.269 0.237 0.299 0.340
Jarrod Dyson 7.6% 14.4% 0.107 0.281 0.248 0.310 0.354 28.6
Ehire Adrianza 7.6% 19.8% 0.101 0.291 0.239 0.297 0.340 37.9
Adam Frazier 7.2% 13.7% 0.112 0.276 0.246 0.311 0.358 42.0
Elias Diaz 5.9% 16.9% 0.100 0.289 0.247 0.290 0.347 49.9
Darwin Barney 5.5% 16.5% 0.107 0.257 0.227 0.276 0.335 52.8
Player stats between 5/27/17 and 5/27/18.

I’m choosing to stop here partly in deference to the length of this article, but also partly because this is probably my favorite table of the bunch. Remember how I said that we wouldn’t see any really good or really bad hitters? Well, that was only partially true. It turns out that in order to find players whose profiles look like the league’s overall performance in 1968, you have to find some hitters who are pretty damn bad. And here they are, all on one list for your viewing pleasure — if I may be permitted to stretch the term.

A final note, before we part: the fifth-lowest difference score here (Barney’s 52.8) is by far the highest of any of the fifth-ranked folks I’ve listed so far, meaning he is the most dissimilar to the comparison line of any player we’ve looked at (by this metric). That’s because, I suspect, playing in today’s game with 1968’s offensive profile just isn’t going to get you all that far, and so very few such players meet my 100 PA/365 day cutoff — though more may exist below it. This makes this year, 1968, just about as far back as we can reasonably go to make this a useful exercise, and therefore where we stop. Treasure these throwbacks while ye May / Old Time is still a-flying.

We hoped you liked reading The Throwbacks Among Us by Rian Watt!

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Rian Watt is a contributor to FanGraphs. His work has appeared at Vice, Baseball Prospectus, The Athletic, FiveThirtyEight, and some other places too. By day, he’s a public policy researcher in housing & homelessness. By night he tweets.

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trevise-en
Member
trevise-en

Well, if you’re doing this for “The Throwbacks Among Us”, shouldn’t you also do one for “The Throwbacks That Were ‘Slightly’ Ahead Of Their Time”…? (hehehe)

fjtorres
Member
fjtorres

The term would be “Forerunners”.
There probably won’t be many because in olden days contact was king, strikeouts anathema, and burners popular.
Ron Bloomberg comes to mind.