XXS vs duration - Forecast AI

I am using Forecast AI to proscribe a training plan for a target event. The planner will indicate a workout with say an XXS of 60 and a duration of 1.5 hours. Then when I click on the recommended workouts - both indoor and outdoors - Xert recommends indoor workouts of far shorter duration but with a XXS of 60. Which do I follow - the XXS/ intensity distribution of the trainer workout or the duration indicated by the planner or both?

Example:
“High intensity training” is indicated by the planner with an XXS of 69 and 1.5 hours duration.
I select an indoor workout and Xert recommends “LTP/Tempo with surges 1-1 wk4” which is only 45 minutes long with 71XSS.
So do I so the indoor workout and then ride for an additional 45 minutes, or do I only do the workout?

Hi @EGoodfriend , great question!

The system tries to estimate how long it will take you to complete the recommended Low, High, & Peak XSS based on the targets themselves as well as your XSS per Hour Preferences. How long it actually takes you to complete the training isn’t really important as long as you hit the XSS targets for the day! You can often achieve the recommended training in less time by doing more challenging high-intensity workouts.

To explore this a bit more, check out the Magic Buckets Workout generator and look at the difficulty & estimated duration of your training at Challenge Level (CL) 2, CL 5, & CL 8 or 9.

Side note: You can’t really expedite low-intensity training beyond Tempo, since increasing the pace/effort means it’s no longer low-intensity :slight_smile:

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Here’s an specific example from my Forecast AI training plan.

Today’s training called for 155 High-Intensity XSS, which was estimated to take 1h56m:

To complete my training, I lead my usual Wednesday morning group ride on Zwift (1h15m of 2.0-2.5), then finished my training for the day using Magic Buckets data field on my Garmin. It ended up taking me just a bit longer, but the estimate was only off by ~10 min on a 2hr ride, so I’ll take it! :slight_smile: