Today TrainerRoad announced radical changes to the platform, which they dubbed Adaptive Training. This means that they are beginning to use machine learning algorithms to change workouts based on their progress toward a particular goal. An exercise is scored as you complete it, and then the rest of your scheduled exercises change accordingly to adapt accordingly. However, although this was announced today, it will not reach most people’s desktops for some time.
What’s on your desktop as of today is the new TrainNow feature, which will give you unique training recommendations across three training categories, based on your previous training history, along with the option to choose your training duration . TrainNow is using the fundamentals of adaptive training machine learning to generate these training recommendations. So, in fact, it’s your first window to the big changes in TrainerRoad.
While this may seem basic, the reality is that, with far fewer people having a set goal to train or compete in 2020/2021, doing ad-hoc exercises has become increasingly common for highly structured athletes. This feature is entirely aimed at those who use TrainerRoad, but without a specific TrainerRoad plan, of which, TrainerRoad says there are more users than you think (although, it works if you have a plan loaded and just prefer to skip the plan)
The main point is that many of us want to do a structured workout, but frankly we can’t decide which one to choose. Whether on TrainerRoad, Zwift, Xert or others – you often receive hundreds or thousands of options with no real guidance or even basic suggestions. In fact, I would suggest that this is why platforms like Peloton have done so well: they bubble up on those exercises suggested for you, removing all indecision blockers.
So, let’s jump right into it.
How it works:
To begin, you will first update your TrainerRoad application and, when finished, click on ‘Training’ on the left side, followed by the ‘TrainNow’ tab at the top:
Next, you can choose a specific duration for your workout, from 30 minutes to 120 minutes. Of course, they align with the specific durations of the TrainerRoad library.
In my case, for today I will choose the option of 45 minutes, and then you will notice how next you change the training options for others. As usual, the fine line in the middle of the workout is your FTP level, so you can quickly assess how much suction this workout will require. Or, those more scientifically focused can simply look at the TSS and IF (Training Stress Score and Intensity Factor) scores listed next to it.
Didn’t like the appearance of the options presented? Isn’t that your favorite blue style? Don’t like the name of the training? No problem, press the ‘Update’ button to wash these options and see three new options. It’s like pulling the arm of a slot machine, suitable for a company based in Reno, Nevada.
Finally, I pressed update a few more times, until I got ‘Goddard –4’, which looked interesting. Side note, you will notice that the intensity and TSS scores for all of these exercises in each category are almost identical. It was no accident. It is also not something for today’s post.
After deciding on a workout, you can tap it to open it. You will have a preview with a little more descriptive details, as usual:
From there, you will pair all training devices and do the training as normal.
And then just go on suffering and do the training as normal. There is no difference at this point – it is as if you did the normal TrainerRoad exercises.
Then, you will get the summary information, as well as see the results in the app and online for analysis there (and also, as usual, synchronized with other training platforms like TrainingPeaks and Strava):
See … easy, easy!
Wrap up:
This is a smart move for TrainerRoad and I have been waiting for a long time to see it. As I said before, the idea of ad-hoc exercises is not very different from what Peloton does, or in fact – even Zwift. For example, on Zwift, when I open the companion app, I see all the next group outings that are about to start. When I decide to do Zwift, 95% of the time I will choose one of these exercises in the next hour or so, based entirely on this small section.
However, Zwift does not have the same concept for structured training. I mean, of course, if one of those group outings is a group workout – then yes. But there is currently no recommendation engine in the constantly expanding library of structured Zwift exercises. And that ignores the fact that it’s a nightmare to find something in the Windows 95-style nested folder scheme that is the exercise UI. There may be a lot of gold there, but I just give up and choose the short or long form of Jon’s Mix in half the time – since I could at least find it quickly in the folders.
But what is probably most interesting on the TrainerRoad side is actually the innocuous text just above the TrainNow exercises, which states: “Allow us to suggest a few other options, based on your recent training history.”
This is notable, because up to this point, TrainerRoad has not taken historical data, except for RAMP / FTP test details, and has done nothing with it that is recommendable or moving forward. Therefore, this single line is basically referring to the major changes aimed at machine learning from Adaptive Training for the platform. But, this is a different thing or two for another day.
With that – thanks for reading!
[Can’t decide on a trainer app to use? Ask no more, and hit up this massively long and detailed cycling trainer apps guide.]