Thanks, @Nate_Pearson! Awesome to see all this data!
I’d love to see FTP:W/kg:Max 1M power … My w/kg sucks… lol
as a data pro, this makes me want to work for you guys! too bad i’m in canada
Can we see a breakdown of Power Records over the population? I.e 99th, 95th, 90th, 50th 25th for 30s, 1min, 5min, 10min, 20min, 60min power?
It would be interesting if you could incorporate this metric (failed workouts) to self reported + tested FTPs in such a way that people could use it to figure out which FTP test is “best” for them. “Best” meaning reports a number that they can use for TrainerRoad workouts successfully.
Yeah, mine was off by about 35 watts
@Nate_Pearson this information is fascinating and inspiring. I have dreams of being competitive at a regional level for mountain biking (maybe see you at Carson City this year ;). With that in mind, I wondered if you can drill down the curve by specialty; Mountain vs Triathlon vs Road etc.
@Nate_Pearson, should be possible to do a bell curve with w/kg increase (monthly? by seasson?)
This is the real question.
“What’s the most effective way to increase my watt/kg for my age, experience, training load and gender”
The answer is already in our data, we just have to find it. Right now, we’re using exercise physiology research to build the best plans we can. I think we can add to that knowledge by finding the correct answer in our data.
It’s tricky though and not straight forward.
Would be better to have it in W/Kg as the raw power number really doesn’t tell the whole story.
@Nate_Pearson This is why I have long thought that TrainerRoad should survey users on everything from nutrition, sleeping habits, etc and then overlay that survey data with the FTP and performance based data you already have to give users an idea of what others are doing that works/doesn’t work. 2-3 questions a month when you login to the website would quickly build quite a bit of data I would think!
I think the ‘helpful’ part of this depends where on the curve you sit. If you feel like you’ve been taking your training seriously for a while (not a beginner, made adjustments to your diet, think about recovery and in general improvement focussed) and then you find yourself left of where you think you should be, I could see that as potentially demotivating.
The flip side of this of course is some kind of enlightenment. My wife is a good example. She doesn’t see herself as athletic, yet has completed 1/2 marathon events and has been a swimmer for years. She has zero interest in bikes or bike riding but once I got my pain cave set up I suggested that she give it a go. An efficient and convenient way to get some exercise in since it’s in our garage. She does not in any way identify with being a cyclist and generally lacks confidence about anything bikes. For her cycling is sitting on the bike and making her legs go around as some kind of Coach Chad marionette. She thinks she’s slow and the fact that my FTP is almost 3X hers doesn’t help her ego (I’m a LOT heavier though ). When I showed her that in fact after only a few months of TR workouts combined with her existing fitness, she is already right in the middle of the bell curve for TR athletes in her age group, she was really surprised. I don’t think it made her any more interested in being a ‘real cyclist’, but it gave her some legitimacy and corresponding confidence that wasn’t there before. Baby steps!
I think we can pull in sleep and weight data automatically from other tracking devices. Nutrition is so hard. No one’s made a good way to track calories easily. If someone can figure that out they’d be an instant billionaire.
Yep, just over 3W/kg.
Really insightful thread @Nate_Pearson kudos to TR for sharing so much data thank you. This is a gold mine of information.
All that quantitative data would be great, but I’m thinking more along the lines of something a bit more qualitative.
A super simple example: “Do you consume some sort of recovery drink after your rides?” When the answer is overlaid with performance data, perhaps we can derive some understanding of what behaviors tend to correlate with performance. Obviously this is imperfect methodology (what constitutes a “recovery drink” for example), but when you compile enough Q&A with performance data I would think it would definitely be useful.
23andme and other DNA testing companies use this all the time. Collect as much survey data as they can, then leverage it with the quantitative data to see what’s relevant.
Anyway, just a thought…
MyFitnessPal? Garmin syncs with it now, could you do the same?
Is the data between various trainers/PMs/virtual power etc…equal? Are we all pushing the same watts?
@trpnhntr Maybe even 401!
I think this is hitting the nail on the head, and whilst you’re right that it will be difficult to find absolutes, I do think a bit of data wrangling could provide some early indicatthat could lead to some interesting experiments if the user base is up for trying them. Just a suggestion.