When viewing previous weeks, it’s possible to see the total “kcal” from the week’s training. I would like to “submit” a feature request to view weekly KJs in the weekly summary. When you click on the left column weekly data, you can see the summary. If the week is in the past (or has training done), it will show the kcal. It would be neat if there was also the KJs listed on the top of this panel/modal. Future workouts all have the KJs listed, so this way users can expect upcoming KJ on a weekly basis rather than a day-by-day basis (or manually adding all the days together)
It might also be interesting to see an expected vs actual for the KJ. So if the training week has an expected 9000kj, and it’s Wednesday where you have 4000kj so far, you could see 4000 / 9000 for example. But mostly just seeing the upcoming/planned KJ per week would be helpful
Those values were not stored on workouts (library) or events (on calendar) only displayed in the app. I have changed that but need to wait a few weeks for people’s plans to get the new fields before displaying anything in the summary.
I’m my view kJ’s are always preferable to calories. Provided your PM is accurate kJ’s are reasonable precise whereas calorie calculations are at best a finger in the air estimate
Part of it is eating related, I like to keep track of things on a week-by-week and day-by-day basis especially while trying to manage losing weight while keeping intensity high.
Concurring with @Cary_Blackburn , I also like to have the KJ in preference of the kcals for caloric burn.
I use KJs more often during base phase along side of training load/TSS to make sure I’m not pushing too far into overtraining territory and that I’m also getting the nutrients (calories) I need. There is some research and metabolic testing such as Bjorn Kafka’s “aerotune” and Alois Mader’s research relating Vo2 Max and protein synthesis to determine how much stimulus (KJ) is needed to adapt and by determining how much overload one can handle.
For example, a rider with a 70 vo2 max may have the best stimulus at 12,000-14,000 kj per week. You can then backtrack and determine how many base hours are needed per week to get the best stimulus for this ride. If every base ride is 210w average, then they are riding at 750 kj / hour. So 12,000 / 750 = 16 hours minimum dose for base training, and 14,000 / 750 = 18.6 hours as the upper-end before reaching over-training territory (if done chronically – a training camp, for example may have more KJ). If the 70 Vo2 rider can’t get 16hrs they may need to add in 1-2 Tempo or SweetSpot rides to get the adaptation they are looking for. On the other hand, if the rider is at hour 15 of 18 in a week but already at 15,000 KJ, it may be a sign they need to cut back on intensity or reduce volume, or take it easy for a couple days before pushing too far… Of course, you can just use TSS and CTL, etc, but sometimes it helps to have another component.
Anyways, there are a few ways to use it. I personally like to see KJ as a “tool” for training load, nutrition, and even monitoring over time to see how your body and RPE handles KJs over a longer scale
This sounds really interesting. Do you have any links to the research you mention please? A google threw up some stuff for Bjorn but not much for Alois. Just want to make sure I’m reading the right stuff.
For sure. One difficult aspect about Mader’s work is that the research is fairly hard to find and when found, it is in German. I am not sure if you are familiar with “INSCYD” test. It’s very similar to the Aerotune of Kafka and co., and was based on Mader’s models of lactate testing.
I think a good way to dive in would be checking out Endurance Innovations and Scientific Triathlon’s interviews with Bjorn Kafka and Sebastian Schluricke, co-founders of Aerotune. They give some good insights into metabolic testing and training in general.
Wow, thank you so much for taking the time to collate all that information! I have downloaded all the pod casts referenced as that’s the best/ easiest way for me to digest. Looking forward to taking a deep dive on the subject
@david I was playing around w/ getting calories data (to mimic your summary) and I uploaded a ride from the BreakAway app and didn’t see any calories numbers.
The “Work” kJ number (icu_joules) is computed from the interpolated power trace. The Calories (calories in the API) number (in kilocalories) is whatever is supplied in the file or from Strava. For .fit files it comes from the “total_calories” field on the session message. For .tcx files it is the total of all the calories fields for all the laps.
You could just use the same as kilijoules and call it an estimated calorie burn. Since 1 joule is ≈0.24calories, and the human body on average is only 25% efficient, then KJ/kCal are practically the same thing as they cancel each other out. Of course if the rider is under-cooling the burn may be slightly higher but as a basic conversion: KJ ≈ Calories
So if my account is linked both Strava & Garmin which calorie figure “takes precedent”. Also would it be possible for you to take the kJ amount (which is obviously very similar) and apply the efficiency factor in Interval.icu itself? That factor could even be customisable in Intervals for anyone who has had a metabolic test done a has a good handle on what their individual efficiency is.
The Garmin number will win but I believe Strava uses the number from Garmin as well so it probably doesn’t matter. I could calculate it in Intervals.icu using a custom efficiency factor as you suggest. I have added that to the todo list.
I really hope that the formula is correct. I’m gonna be using this for the TCX/FIT file generation.
I cross checked the data using outputs from Garmin and they seem to line up correctly
If anyone here can help confirm it, that would be great.
Thanks!
. Aspects of protein synthesis are covered in the book and should have enough info on the website as well. One user in another forum pointed out that Mader’s model is actually fairly simple, and you can get much more complex models to stimulate the cell, for example, this study here: 
