f a i t h * i n * f i c t i o n: Day 1 of Imaginary Metrics – The Tyranny of “Our Way”

f a i t h * i n * f i c t i o n

Monday, January 17, 2005

Day 1 of Imaginary Metrics – The Tyranny of “Our Way”

People get cranky when someone tells them they aren’t doing something right (or well) that has served them (seemingly) just fine for as long as they can remember. Often, faced with a suggestion or recommendation to change, they can get down right irrational.

Case in point: me. My wife, (who’s rather the textbook definition of a “better half”) during the early months of our marriage, suggested at some point that the way I washed dishes might not be optimal. I wasted a lot of water. My reply, which I framed delicately and with much maturity was, “You don’t like how I was dishes? I won’t wash them.”

We’ve straightened me out a bit since then. I think. But the lesson stands.

The same thing has happened in the field of baseball over the last two decades. It used to be that statistics like Batting Average and metrics like Runs Batted In were the numbers by which quality play was quantified. If you hit .300 and had 95 RBIs, that was a heck of a year.
In the last 20 years, statisticians have been coming up with new statistics and metrics that are challenging old wisdom. They aren’t saying that using Batting Average is wrong—just that it is incomplete and does not provide the best data available to make judgments on quality. On Base Average, which includes walks, does a better job of speaking to a batter’s worth because it includes EVERY time a hitter is on base—and since you can only score when you’re on base, you need to speak from that position.

Likewise, RBI’s are fine, but they are more a comment on how often a player’s teammates are on base. Slugging Percentage becomes a more useful metric because it manages to leave out data that muddies the water.

Adding On Base Average and Slugging Percentage together gives OPS (literally, on base plus slugging) a very simple short hand method of distinguishing batter’s overall offensive worth. But you don’t see this reported in newspapers; you rarely hear it mentioned on television. And only some teams feature it in their own press materials.

Why? Because it’s new. And it challenges traditional statistics that have filled the backs of tobacco and bubble gum cards since baseball’s earliest days. That’s a lot of heritage to overturn.

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We aren’t fighting against centuries of statistics in looking at writing with a mathematic eye. Instead, we’re faced with millennia of not applying statistics or metrics at all to novels. Writing is art and craft and to dissect like the latest corpse on CSI seems to many to be as foolhardy as trying to catch gossamer. To others, the novel is like Schrodinger’s Cat, falling to pieces the minute you try to examine it.

I guess I don’t agree. We have centuries of writing available to us. What patterns might be revealed in the tapestry of all those words? What algorithms drive the beating heart of popular literature since time began?

Over the next four days I’d like to discuss at least four measurable metrics that I think would have a lot of importance to us. These are going to be theoretical, for the most part, but at their core will be an inductive way of looking at novels that may give us a new perspective on things.

Tomorrow we’ll look at a metric discussed briefly on Friday—Overall Dialogue Percentage. Is their a golden number after all?
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Continue to Day 2 of Imaginary Metrics