Using RPE to get Stronger on the Bike
Over the last 20 years power data has completely transformed cycling. When I first began coaching cyclists in 2010 I was begging my athletes to invest in this thing called a power meter.
At that time people were still on the fence as to whether or not the power meter was a passing fad or a truly indispensable part of the bike. Fast forward 10 years and power meters are nearly a standard feature on every high end bike.
For most cyclists, the objectivity of data is not only a huge asset in their training, but it makes riding a bike more fun. Objective data is great but the pendulum seems to have swung a bit too far, with many cyclists having a hard time understanding their effort without the screen on their Garmin.
For this reason we’ve been talking a lot more about the other end of the spectrum, a subjective rating of perceived exertion (RPE).
RPE is helpful because it takes into account all of the external and internal factors that contribute to your cycling performance. Learning the language of RPE has the potential to be just as important to your cycling as your power meter.
If you’re looking to improve your riding, the best way to add balance to the razor sharp specificity of power data is to invest in learning more about how to utilize RPE in your riding.
From the Blog
If you want to read more about RPE head over to our website and check out our most recent post on the topic. If you’re short on time here are 3 highlights from our post.
- Get comfortable using a simple 10 point RPE scale (you can download the one we use over at our site)
- Plan your hardest workouts during times when RPE might be lowest
- Don’t let power targets hold you back, let competition drive your performance to new heights
If you want to check out a more in-depth presentation on RPE head over to our 6th episode of DDA live where we cover the topic in a bit more depth. You can check out our DDA Live presentation by clicking here.
Best of luck as you work to add a bit more subjectivity back into your cycling!
Data Driven Athlete