Would Sabermetric Principles Be as Fun If Applied to Other Things In Life?
I’m sure this question has been asked before. By all of us. Maybe on an everyday basis, even.
An e-comic strip, submitted by reader Aaron E., imagines what the application of sabermetric principles would produce if applied to comic books:
KARP, or Kills Above Replacement Villain, actually sounds like something that I would like to know about, were I an avid reader of comic books. I see all the comic book movies, so I am interested in such a metric for those purposes, but you don’t really see replacement-level villains in the movies like you would if you got every issue of a comic. Seeing a comic book movie is like watching only the World Series, or better, only the All-Star Game. The idea of KARP actually sorta makes me want to start reading some comics — or studying some comics.
I’ve been a baseball fan since I was five years old when I started collecting baseball cards, but my fandom was taken to a new level (a level that one’s significant other or family might call “extreme” or “obsessive”) in 2004 when I started reading Bill James and Baseball Prospectus and the like. In my opinion, sabermetrics has increased my enjoyment of baseball –something that I already loved — manyfold.
So what else do I love that might be improved by such metrical scrutiny?
I love comedy, for one thing. Humor is more subjective that baseball: runs are scored, games are won — no one can argue with that. But since this is personal, so I might simply ask, What sort of comedy do I enjoy most? One thing I enjoy is a good dong reference. I like anything pertaining to the groinal region. Also, “boobs” is a funny word.
I can imagine a “stat” — call it DONG% — that documents what percentage of comedian’s jokes are (or time on stage is) about genitalia. This is sort of the xFIP of comedy for me, because for a lot of comedians, DONG% is not going to match up with my actual enjoyment of a comedian. The correlation between DONG% and something like L% (percent of time I spend Laughing during a set; perhaps comparable to RA/9 in baseball) might even be statistically insignificant.
What would be interesting to me is discovering which comedians have the biggest gap between DONG% and L%. Then, I could do more qualitative analysis of those comedians to find out why I don’t like them as much as (or like them more than) DONG% might suggest. If this leads to producing additional information about comedians — e.g. what kinds of dong jokes they are making (perhaps akin to Batted Ball data) — then perhaps this information could begin to help other people understand which comedians they will prefer, or why they prefer the ones that they do.
I think that such stats would not ruin my visceral enjoyment of comedy, and that they would allow me to have more interesting conversations about comedy with people who are similarly interested or inclined. I like having conversations.
The time that it would take to compile such stats would probably not be worth the benefits. With baseball, you have thousands of people who are working — often together — to compile, analyze, and interpret stats which can then be used by individuals for their own purposes: fantasy baseball, conversations, avoiding life’s other obligations. With something like comedy, many of the stats generated (e.g. L%) would have to be based on individual tastes of each audience member — though there are some stats that would be more objective. If there was an infrastructure to compile such stats, I would help to compile them and definitely consume them.
One can imagine how sabermetric principles can be applied to so many things. There would be all sorts of ways to quantify the “success” of films, actors, directors, or producers. And so on.
What’s your fancy?
There should be a statistic that estimates your probability of getting a girl’s phone number in a given situation. It would have to include Bayesian priors like what clothes you are wearing and your height, etc. It could be called pLAY or something.
Incidentally, the pLAY of a sabermetrician asymptotically approaches zero.
So you’re sayin’ I have a chance!?