The following is an excerpt from an upcoming book on technology, distraction, and why training simply is the most effective way to improve your cycling. To get updates and follow the progress of the book please sign up for our newsletter.
One solution to cycling drudgery is to stop striving all-together. A more passive approach to riding might reduce expectations, but is unlikely to result in the moments of flow that often define our best experiences on the bike.
The better alternative is to resist the tendency for our rides to be held hostage by future goals, focusing first on enjoying the present moment on the bike [1].
A narrowed perspective defines the autotelic cyclist: a rider that appreciates training for its present moment value, rather than viewing it as a compulsory burden required for future greatness.
This shift in thinking runs counter to crowd-sourced training wisdom that seems to advocate for constant internet foraging of training strategies and hacks, all as a means to an end.
The voice in your head might be saying, “cute story, but training is miserable, most of it sucks, and hating large swaths of ride time is a requirement for getting stronger, faster, and winning more.”
I’m here to tell you that that voice is wrong. There is a better path.
An autotelic approach to cycling won’t transform every moment into bliss, but it will signal a shift in how you approach the broader framework of your training.
Reducing your training to watts, interval progressions, and periodization schemes is no longer adequate. Training must be part of a more substantial exploration of the bike and what it means to be alive.
Cultivating the joy of riding, while striving for greatness is the primary training challenge this book seeks to address. We get there by focusing on less.
Training can be confusing. In our free eBook, we’ll show you four ways to use your data and insights from science to ride better than ever.
Nate Dunn
Founder/Head Coach
Data Driven Athlete
References
- Csikszentmihalyi, M. (2009). Flow: The psychology of optimal experience. New York: Harper [and] Row.