WKO4 is a data analytics engine from TrainingPeaks. I’ve used it for the past season to dig into my numbers and optimize my training. I find it invaluable in revealing gaps in my fitness, and quantifying where I can improve and how I should target that improvement.
Here is some of the analysis I have done for my own 2017 Season Review.
Bear with me.. some of these charts get complicated (of course!).
Aerobic Power-HR Relationship
This is a highly customized chart inspired by Tim Cusick and the other chart wizards behind WKO4. It shows an ongoing weekly summary of the Aerobic Power & Heart Rate relationship through the 2017 Season. I’m specifically looking for trends in Power and HR just below the Aerobic Threshold (AeT) where you would train for Aerobic endurance.
- The yellow bars show Weekly Average Power when HR is under my Aerobic Threshold HR (AeT HR).
- The top red line shows Weekly Average EF (Efficiency Factor; a measure of cardiac efficiency).
- The bottom pink-ish line shows Weekly Average HR when power is under my Aerobic Threshold Power (AeT Pwr).
HR and Power are indirect and imprecise measurements used to estimate Aerobic metabolism.Remember, true indication of AeT and Aerobic metabolism is determined in the lab via respiratory gasses and/or blood analysis. But together, HR & Power can be used to kind of triangulate the crossover point (AeT) from pure Aerobic, into glycolytic metabolic processes.
In theory, AeT HR should match AeT Pwr for steady state efforts. However both measures are too variable to perfectly display that crossover point. It does still show the directional relationship between Power and HR around AeT and more importantly, the trends in this relationship over time.
- Weekly Average Power and Weekly Average EF should both increase over time with greater Aerobic adaptations, as I begin to produce greater power output for the same HR ‘cost’.
- Weekly Average HR should decrease over time as I can produce the same power output for a lower HR ‘cost’.
- The observed trends (dotted lines) match the expected improvements with greater Aerobic adaptations over time.
- For instance, early in the season it takes me 138 bpm to produce my AeT Pwr. Toward the end of the season it only takes me 130 bpm to produce the same power. Meaning my training gave me an extra ~8 bpm with which to produce greater power!
Tracking the Aerobic Engine over Time
Referring back to the first 2017 Season Review post, note the cursor highlighting April 22, which was when I reached peak CTL (122 TSS/day). This coincided to my peak Average Weekly Aerobic Power before tapering down toward my target races in May & July.
Then once Race Season begins the numbers become more variable as fatigue and the demands of racing takes it’s toll on my Aerobic Pwr-HR relationship.
Training the Aerobic Engine
Training to increase your Aerobic Threshold Power (AeT) primarily has to be done by pushing AeT up from below: working for long durations at sub-AeT workloads to increase the number and efficiency of your Aerobic muscle fibers.
What I’m still looking for is establishing prescriptive protocol for optimizing efficiency of Aerobic adaptations with the least amount of time spent training per week. This would be incredibly valuable to be able to give expected norms for, eg. percentage adaptations above baseline given x training hrs per week at sub-AeT workloads.
Recently I’ve come across some compelling literature that begins to narrow the focus for Aerobic training prescription. I’ve followed up with a post about what I’ve learned. Please read on!