Diagnosing an Obsession

Me, making an odd face in the redwoods. Wilder Ranch, Santa Cruz, CA

Before starting this blog, I would spend hours each day scrolling through used mountain-bike postings.

In fact, I came up with this September writing challenge as a way to get myself to spend less time looking for deals when, in fact, I am not remotely in the market for a new bike. That, and playing an obscene amount of League of Legends. A little over two weeks out, it’s worthwhile, I think to look back and ask how things got to that point in the first place.

I started mountain biking in August of last year. I had taken up road biking slightly less than a year before that, and had purchased a gravel bike on a whim at the start of the COVID-19 pandemic. I was fit enough from road cycling and surfing had given me a sense of how to work with gravity to find a state of flow. I found a great deal on a bike while I was visiting my family down in Southern California, and straight away I was hootin’ and hollerin’ my way down the local trails.

From that point on, it should have been happily ever after: I had a great bike, a ton to learn, and the time and trails to do all the riding I wanted to. But I was also a mega-nerd. I couldn’t just ride my bike, I had to absorb as much information about this sport as I could possibly find. I started listening to mountain bike podcasts in the car and in the shower. I watched YouTube videos on technique and technology making my morning coffee and laying in bed in the evening. It got to the point where I would call up bike shops just to have someone to talk about bikes with.

To give you a sense of the breadth of obscure knowledge I’ve amassed on this topic, here’s a list of bike models I can name off the top of my head. No googling, I promise 🙂

(In order from least to most travel, to the best of my knowledge)

  • Santa Cruz
    • Stigmata (gravel bike)
    • Highball
    • Chameleon
    • Blur
    • Tallboy
    • 5010
    • Hightower
    • Bronson
    • Megatower
    • V-10
  • Specialized
    • Diverge (gravel bike)
    • Fuse
    • Epic (and Epic Evo)
    • Stumpjumper (and Stumpjumper Evo)
    • Enduro
    • Demo
  • Trek
    • Checkpoint (gravel bike)
    • Top Fuel
    • Fuel EX
    • Remedy
    • Slash
    • Session
  • Canyon
    • Grail (gravel bike)
    • Grizl (adventure/gravel bike)
    • Lux
    • Stoic
    • Neuron
    • Spectral
    • Strive
  • Transition
    • Throttle
    • Spur
    • Scout
    • Smuggler
    • Sentinel
    • Patrol
    • Spire
    • TR1
  • Evil
    • Chamois Hagar (gravel bike)
    • Following
    • Offering
    • Wreckoning
    • Insurgent
  • Yeti
    • SB-110
    • SB-130
    • SB-140
    • SB-150
    • SB-165
  • Norco
    • Torrent
    • Optic
    • Sight
    • Shore
  • Revel
    • Ranger
    • Rascal
    • Rail
  • Commencal
    • Meta HT AM
    • Meta TR
    • Meta AM
    • Clash
  • YT
    • Izzo
    • Jeffsy
    • Capra
    • Tues
  • Orbea
    • Occam
    • Rallon
  • DeVinci
    • Troy
    • Spartan
  • Giant
    • Trance
    • Stance
  • Pivot
    • Trail 429
    • Switchblade
    • Firebird
  • Ibis
    • Excee
    • Ripley
    • Ripmo
  • Propain
    • Hugene
    • Spindrift
  • Guerilla Gravity
    • Trail Pistol
    • Shredd Dogg

Wow, that was actually quite satisfying. Not in the same way as a hearty meal or a job well done–it was more like pulling a splinter or finally throwing up after feeling queasy for an hour.

If you read through my entire regurgitation, thank you. If you skipped to the paragraph above, I understand and respect that. If that list doesn’t already have you overwhelmed, consider that each of those bikes comes equipped with a particular fork, shock, handlebar, seatpost, tire combination, set of brakes, set of wheels, shifters, rear derailleur, chain and cassette, seat, headset, and grips. On mainstream bikes, the majority of those parts are made by either Shimano or SRAM, but both companies offer several levels of quality to match different price-points. On top of that, there are dozens of boutique parts-makers that snobby bike people rave about. Tire companies have different tread patterns, casing compositions, and sidewall thicknesses. Then there is the world of geometry, understanding how the various angles and lengths of the bike frame influence the type of ride on offer. And don’t even get me started on suspension design, leverage curves, and anti-squat.

It’s a rabbit hole if I’ve ever seen one, and I was going down, down, down, the bottom nowhere in sight. Remember that I’ve only been doing this activity for a little over a year, and I’ve only spent significant time on one bike. But the world of used bikes lets me do something with all the knowledge I’ve accumulated.

I can look at a bike someone else has built, and using this arcane encyclopedia I’ve assembled, come to conclusions about how it would ride, what kinds of trails it would be suited for, and whether the asking price is fair. I imagine that this is how a neural net feels, after being shown millions of pictures of dogs and cats, when it finally gets to look at a picture and say whether it is a dog or a cat.

That one’s a cat.

That one’s a dog.

That one’s a great buy if you live in the Pacific Northwest and descend more than 2,500 vertical feet on an average ride.

The funny thing is that I, like all humans, am severely limited creature, computationally speaking. I have limited processing power, speed, and, crucially, memory. So what was tossed in the dumpster to make room for all of the mountain bike minutiae? Childhood memories? Song lyrics? Email passwords?

I expect that one day I’ll find out. Or perhaps I won’t. I’m not sure which would be worse.

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