I've written a bit before about the fact that baseball is, first and foremost, a form of entertainment. The benefits we derive from baseball are limited to its entertainment value and anything that might be derivative of that entertainment value (say, for example, players' salaries).
But it wasn't until I came across this particular sublime bit of manic meandering from fellow traveler Carson Cistulli that I got it figured out. You see, folks, we enjoy by categorizing. And the ultimate categorization is the definitive metric, the holy grail with the mass appeal.
We might not be happy until we find it--and we might never find it.
Table of Contents
As I said, I was inspired by Carson Cistulli, who had this to say about the enjoyment of baseball:
Are we doing the best job of enjoying baseball as possible? Are we being efficient with our time spent watching baseball?
It's important here that when he says "we" he means something like "readers of Fangraphs" (or BtB, for that matter). Cistulli's question, though, is worth asking. If we could approach the game in a different way, or experience it another venue, or do it in the road and have a better time, then we probably should.
Cistulli also notes:
[M]y concern isn’t ever with the site’s excellent player analysis or sweet use of Pitch f/x technology, per se. Those things are great, yes, but ultimately, the reason I point my internet browser this way — the reason anyone would — is because I find it pleasing in some way. Restated: I’m interested in reading FanGraphs, in particular, and statistical analysis about baseball, generally, only insofar as it adds to my enjoyment of baseball and my overall happiness.
And there we have it summed up nicely. It's all about enjoyment. The goal, as an economist would say, is to maximize utility subject to constraint. Of course, maximizing when you already have a function is a (ahem, relatively) trivial matter of partial differentiation. But what is the function?
That's the question:
I wonder if we could produce something like a linear weight of baseball-related pleasures [that would include] anything that could potentially bring joy to a spectator: the vertical movement of a fastball, the True Distance of a home run, even the joy of anticipation associated with a rookie’s debut. There’d be a number that could predict the relative entertainment value of a game, which could predict how many moments of pleasure I might derive from said game.
It got awkward, right?
Stop me if you've had this experience before: you're geeking out about something new. You're excited by the possibilities, the extension of the idea, its possible applications. You start talking with friends about it, and your excitement multiplies, and then out of nowhere, someone suggests taking it too far. The Quantification Urge is particularly prone to this type of phenomenon, and there can be no doubt that it can be taken too far.
So the question is: how do those of us who feel the Quantification Urge use it to maximize our enjoyment?
First, let me take a step back and explain what I mean by the Quantification Urge. If you've ever read Asimov's Foundation series, you know what I'm talking about. (If you haven't, please see the man at the door, who will revoke your nerd privileges.)
The central premise of the Foundation series is that the Galactic Empire is in decline (what self-respecting empire isn't?) and the only man who has predicted it is Hari Seldon, the inventor of the science of psychohistory. Psychohistory is a branch of mathematics concerned with predicted human events on the largest of population scales and time horizons.
Using psychohistory, Seldon has predicted that, absent intervention, the Empire will collapse and will be followed by a thirty millennia interregnum of chaos and darkness. You know, the WORST. His plan, meticulously conceived, promises to abbreviate the Dark Ages to just one thousand years.
(The premise was adapted from Gibbon's History of the Decline and Fall of the Roman Empire, with substitutions made of psychohistory for Christianity and reason.)
You can imagine why a fantasy where a mathematician first predicts, and then prevents, 29,000 years of human suffering would appeal to someone who likes baseball statistics. When an Imperial interlocutor questions Seldon why he cares about events so distant from his own experience, Seldon responds:
I shall not be alive half a decade hence, and yet it is of overpowering concern to me. Call it idealism. Call it identification of myself with that mystical generalization to which we refer by the term, "man."
The point of all this is to show that there is an urge, among a certain type of person, especially mathematicians, to use their knowledge for the general good. And it is that general education (paired with the search for knowledge) that gives that sort of person enjoyment. It's the saving of others from their mistakes (RBI and batting average) that gives satisfaction.
That's why sabermetricians care not only about finding a single, definitive metric but also of proselytizing advanced metrics to the general baseball community.
So I suggest this Quantification Urge exists at all times (even in the future!), but is given specific venue in sabermetrics. And it has been recently stoked by Joe Posnanski and his search for a single, easy-to-understand statistic.
But Colin Wyers (who, by the way, deserves a Viking funeral as he leaves THT), never one to miss a chance at the last word, is filled with righteous Quantification Urge.
It would be difficult to do justice to his proof technique by excerpting here, but he begins with the familiar concept of Runs and RBI and somehow ends up at linear weights.
He begins with what we are all used to, but we also know is wrong. Then he makes adjustments for how often things happen and how many bases they advance runners, and penalizes for outs, adds a little pixie dust, and the result is the most reliable form of run estimator we've got. Is it going to convince everyone? No, of course not. It's got tables, and the mere tabulation of data frightens a great many people. But at the very least, it's a neat parlor trick.
I said at the top that we might not be happy until we find a metric that is both accurate and capable of gaining mass acceptance. Wyers' Herculean efforts (and the efforts of others) demonstrate just how difficult a task that really is. In fact, accuracy and mass appeal often appear to work at cross-purposes (ever tried to explain Base Runs?).
But I am optimistic that we can enjoy baseball and sabermetrics even if the task turns out to be impossible. Like all great tasks, there is no way to prove whether it is possible other than to succeed. Conversely, one cannot show that the task is impossible!
So we go on boring people who engage us in conversations about baseball by giving them way more than they could have expected or wanted. The result is twofold. First, it makes us feel better, and increases our enjoyment of the game. Second, it's their fault for listening.
So let's speculate: will it ever be possible to conceive of a widely-accepted advanced metric that accurately describes run scoring?