Hey everyone!
AI FTP Detection is now available in Early Access. We know that testing (assessing) can be stressful, and we’ve been hard at work devising a better way. This feature replaces the need to test by using AI to analyze your training progress, previous experience, and many other factors to give you an informed and data-backed FTP.
How To Enable AI FTP Detection:
Step 1. Log into the TrainerRoad website
Step 2. Access Account then Early Access from the navigation menu
Step 3. Under AI FTP Detection, select Enabled
Step 4. Proceed to the apps to use FTP Detection
How To Use It:
Step 1
Make sure you have at least 12 TrainerRoad workouts or have imported outside rides with power data. If you don’t have 12 workouts or haven’t imported rides, don’t worry. You can still enable the feature in Early Access, and the feature will automatically become available once you complete 12 workouts.
Step 2
Once you’ve enabled Early Access for AI FTP Detection, open the latest version of the mobile or desktop app.
Step 3
When a Ramp Test is your next scheduled workout, go to the Career tab in the app. Select Use FTP Detection to be presented your new FTP.
There are two reasons that may prevent us from detecting your FTP. First, your data may still be processing. If so, close and relaunch the app after a minute. Second, your FTP has changed within the last 14 days.
Step 4
Select Accept to use the new FTP. Your Progression Levels will be updated automatically, and a workout will replace the Ramp Test on your calendar.
For more info, check out our support article.
FAQ
How is this different from FTP updates on other platforms?
Most other platforms use what we call capacitive efforts to estimate your FTP using an FTP estimation model. This means that they rely on you to complete all-out efforts within your training data.
For example, if you had a very hard 20-minute climb during a ride (ridden at ~ 105% or greater of current FTP), they might use that effort to estimate a higher FTP. Our model does not rely on capacitive efforts. Instead, our model predicts your FTP based on your training history and your personal biometrics.
Will AI FTP Detection consider unstructured outside rides as well?
Yes. AI FTP Detection takes into account all rides with power or HR data.
Do I need to use a heart rate monitor?
Nope! All you need is consistent, structured training with a power meter or VirtualPower. If you’re riding without a power meter, wear a HR monitor. We recommend you wear a HR monitor on all rides for data collection for future potential features.
Can I still complete an FTP Test?
Yes, you still have the option to complete your scheduled Ramp Test.
How do I know AI FTP Detection is accurate?
The best validation for your detected FTP is whether you can successfully complete Productive workouts after you accept the new FTP. If that is not the case, we want to know about it.
What does AI FTP Detection look at to detect my FTP? What types of efforts or workouts does AI FTP Detection consider?
AI FTP Detection looks at your training history and your biometrics to detect your FTP. Because AI FTP Detection considers so much of your training data, it’s very unlikely a single type of effort or workout would substantially sway the model. You don’t have to do capacitive or all-out efforts for the feature to work. In fact, it works if you only do sweet spot or aerobic riding!
Does this use or estimate the Ramp Test result?
AI FTP Detection’s goal is to give you a training benchmark (FTP) that gives you the most productive training. Rather than looking at a single effort, AI FTP Detection uses many factors to provide an FTP that ensures that your training is scaled to your current fitness level. You do not need any FTP tests in your training history to use this feature.
Can one ‘standout’ ride or effort impact my detected FTP?
This is what sets AI FTP Detection apart from other FTP estimation tools. Because our model looks at your training history more holistically, an outlier ride or effort will not unduly influence the model. AI FTP Detection will consider outlier rides and efforts, but will not depend on them to detect your new FTP.
How can AI FTP Detection be accurate if I’m just returning from an offseason or more than one week off the bike?
AI FTP Detection was trained on an enormous data set and can predict decreases in FTP even after long (weeks to months) training interruptions.
I use a different power meter for my outdoor rides than for my indoor rides. How will FTP Prediction handle any differences between the two power meters?
This is one of the benefits of using a model as opposed to using an estimate. We don’t simply estimate your FTP based on outdoor power data (which is often reads higher than indoors). Instead, we include your outdoor power data in addition to the various data points we already have to predict your FTP.
Edit to add updated info from Amber, 23 June 2022:
