My Polarized Training Experience (Chad McNeese & others)


That’s only a recent change, plus not all users bring their outside rides in to TR, so I think the “meaningful” data set is relatively small.

1 Like

It may be “recent”, but mine (and I am guessing many others) had TR pull in all of my prior outside rides.

Actually, I have everything from BEFORE I even started with TR (4 years of data with only 3 years of TR history). So I have much more than just what I did after the outside import feature was added.

We all concede that it is not “conclusive” and I already stated as much above. But I still think that some great info and direction can be gleaned from the data they posses.


I’d like to know how TrainerRoad’s own data could possibly be used to show anything other than improvements were made when people followed their plans. That is not in question here.


I can envision plenty. Seeing trends in a single athlete vs similar population (age, weight,)… particular gains (or lack there of) from one plan vs another… trends in consistency vs volume vs actually hitting workout prescription…

Lots of stuff. There are likely many, many ways to slice the data. Differences in magnitude are potentially as important (if not more so) in looking for making decisions about plans, workouts, etc.

It’s not all-encompassing, but it isn’t worthless either.


Considering most of these studies that are used to “prove” how effective POL training is usually consist of like 50 riders total over about 8 weeks, I’m willing to bet TR’s own internal data is at least more robust than that.


At my day job we do a lot of data science on data that would be considered a lot more incomplete than TrainerRoad’s user data. In fact, on one project, we’re able to tease out trends from data that is recorded by hand on paper as natural language comments.

I’d love to get my hands on the TrainerRoad user data. I’d wager we’d be able to do all kinds of neat stuff with it.

1 Like

A concrete example that would be super easy to implement is a ftp increase prediction. It could look at age weight ftp and attributes of previous and planned training to estimate ftp improvements. I wonder if this could be done with any amount of accuracy.


While I think there will be brilliant data on trends within the TrainerRoad universe (and I’d very much like to see it) I can’t see how they would have enough concrete data to make any justification for polarized vs sweetspot, which is what we’re talking about here.

I can’t see how it’s possible to go from a discussion trying to justify whether a reasonably controlled but limited study is valid or not to expecting answers from TR’s uncontrolled data.



Trainerroad’s Big Data and what it could tell us would be great topic by the way. I might start it when I get home.


When @mcneese.chad does his ramp test next week, I think we’ll know the answer on POL vs THR, and we can put this issue to bed :stuck_out_tongue_winking_eye:


I agree that you probably cant use the data to prove ss is better than pol. However what you could use the data for is to predict what type of training would be better for a person. Granted i have no idea what the accuracy would be but the framework would be simple enough to set up.

1 Like

Yes, I’d love to see that.

1 Like

Not until he’s detrained and completed the crossover sweetspot plan…


And then repeat the comparison so that we’re sure

1 Like

You guys mapping out the rest of my season… for the benefit of all… of course??? :stuck_out_tongue:

I wish my time and data would prove so useful for everyone :wink:
but it’s likely to be entertaining at best for everyone else.

I had free time and It was fun to try a different approach at the very least. I do think there may be some takeaways, but we may not see them until I hit the ramp next week and see how I feel in the Disaster-Half test.

Fun either way and kept the conversation going while we continue to wait for the big TR info.


We won’t really know anything for sure until we clone you and have your clone run the standard trainerroad program concurrently.


Now your’re talking.

Afterwards, I can use him to do all the other junk I don’t want to do (mow the lawn, empty the litter box… and so much more).

1 Like

A bit like the Yates brothers?

1 Like

There’s a interesting discussion on the Xert FB about Fat/Carb ratios which are related to Vt1 & VT2 thresholds The guys at Xert constructed a graph from Froomes GSK lab report which shows his Fat/Carb ratios against his power and various thresholds. FB_IMG_1541070395466


Can you post a link for this Xert article?