Published May 10, 2020 · Updated Jul 25, 2020
We recap the results of following AI Endurance’s cycling training plan that saw our FTP grow according to AI Endurance’s predictions, following the instructions on how to improve FTP.
We - Dominik and Markus of AI Endurance - have been training for Paris to Ancaster 2020 , a gravel grinder race that was supposed to happen on April 26th 2020 but was cancelled because of Covid-19.
Nevertheless, we stuck to AI Endurance’s 8 week cycling training plan and saw great improvements. If you missed earlier posts about our journey, you can find them here:
Dominik grew his FTP to 283 W in 8 weeks, slightly better than the prediction of 261 W, achieving a new PB with AI Endurance’s individualized training plan. His thoughts:
Markus grew his FTP to 299 W in 8 weeks, also slightly better than AI Endurance’s prediction of 293 W. His thoughts:
Check out Markus’ FTP test on Strava:
Also, see how his FTP improved over time compared to AI Endurance’s predictions:
Don’t waste your time with one-size-fits-all training plans. Use AI Endurance’s predictive data-driven approach instead to improve your FTP and get that PB! Get your own personalized training plan today!
DFA alpha 1 lets you estimate your aerobic and anaerobic thresholds from heart rate variability, with no lab test and no dedicated test workout. A chest-strap HRV monitor like the Polar H10 is all you need for heart-rate thresholds; add power or pace data and you get corresponding thresholds in watts or pace units too. Here is how it works and how accurate it is.
by Markus Rummel. We present the first results of AI Endurance's new capability to calculate Respiration Frequency (RF) from in-activity heart rate variability (HRV) data. RF demonstrates its potential in assessing the validity of HRV threshold determination.
Track your aerobic and anaerobic thresholds from DFA alpha 1, the heart rate variability metric, with the AI Endurance app. This guide covers every device that records it: Garmin and Suunto watches and bike computers, the Hammerhead Karoo with our on-device extension, and the Apple Watch with Watchletic.
by Markus Rummel. Last month I presented our durability research at the Science in Cycling symposium in Bromont, Quebec. The question behind the talk: can you measure how well an athlete holds up over a long ride from the data they already record in training, without a lab test? In other words, can you measure your cycling durability from everyday rides? The short answer is yes, and this post explains how, what we found, and why it matters for your training.
