S.T.O.K.E.

Here’s something I’ve always wondered:  Why do things lose their luster?  I’m not just talking about precious metals (I guess there’s a pretty scientific explanation for that).  I’m talking about people, things, and activities. 

Have you ever met someone that you like every once in a while?  Or you’ve said “I can hang out with him for a weekend or so, but any longer and I get kind of sick of him.”  But if you go a couple of months without seeing the guy, you wonder what he’s up to, and you want to connect with him again (but not for too long . . .).

Or you buy a new toy that is supposed to be awesome, you use it for a couple of months, and then it starts collecting dust.  I can’t tell you how many times I’ve seen someone’s Nintendo Wii pushed to a dark corner of an entertainment cabinet, not even plugged in.  I don’t remember the last time I used mine.

And even activities are like that.  I want to go skiing so much right now, I’m actually thinking about driving the 4.5 hours to Sunday River to fight 200 other people on a run covered in snowguns blasting my face off.  I’m not going to do it, but the fact that I’m even considering it is ridiculous.  But by the spring, I can’t be bothered to ski on a day that isn’t springerific (a word I just made up to describe a perfect spring day – which may encompass anything from soft corn to 3 feet of cold powder).  If it’s icy, rainy, or cold, I find something else to do.

I recognize the Law of Diminishing Marginal Utility (which basically says that you get less and less benefit from each additional plate of food you get at a buffet), but I don’t understand why some things seem immune to the rule.  I mean, my Wii doesn’t get used anymore, but my mountain bike definitely does (finally back from the shop – nice).  And my previous skiing trip doesn’t make me want to ski less; it makes me want to ski more.  With that in mind, I’ve developed the Skiing To Orbiting Knobby Equations, or S.T.O.K.E. for short.  Taking a variety of factors into account, I constructed the following Formulas:

Skiing Stoke = log₁₀(0.7s + 0.17A^1.5 + 0.1E² + ln[0.4d_b] - 0.1t)

MTB Stoke = log₁₀(0.17A^1.5 + 0.1E² + ln[0.4d_b])

Where s is the amount of snow on the ground, A is anticipation, E is probability of an epic day, d_b is the likelihood of a beautiful day (when you go out skiing or riding), and t is the probability that I might have to teach when I go to the mountain. Each of these variables is a value from one to ten depending on the month.  For example, October has a 10 anticipation factor for skiing, but only 1 for mountain biking.  February has an 8 for amount of snow on the ground, but only a 4 for beautiful days.  For skiing, March gets a 6.5 for epic days because I figure there’s a 65% chance of an epic day when I go skiing in March (counting days that I miss work to ski a Powder day). 

Using these data, it is possible to graph my Stoke for skiing and MTB over the course of the year:

As you can see, there is a noticeable dip in the Ski Stoke from December through February.  This drop in stoke is almost completely attributable to the likelihood that during those months, whenever I’m at the mountain, I’ll probably be teaching lessons instead of freeskiing.  Also of note is that in March and April, while my skiing stoke is at its peak, my mountain bike stoke is pretty high.  This is probably due to the fact that it’s possible that I’ll get a day or two of riding in during those months.  As high as my anticipation for the ski season is in August and September, I’m (most likely) not going to be getting any ski days in.  Therefore, my stoke for skiing doesn’t rise as quickly as my stoke for MTB.

Additionally, this graph proves one more thing about my skiing and mountain bike riding:  with the increasingly short days, I have way too much free time on my hands.  Maybe I’ll go play some Wii.