In threads where training philosophy comes up, discussions of TRIMPS and TSS and other training models occasionally intrude. These models are not very well known, and even more poorly understood, so probably SolarEnergy, qbrain and I are just talking to each other and killing threads in those conversations. In any case, I figured I would present a brief overview of what it is that we're talking about when this terminology starts showing up.
Best case, this will introduce these models to the subset of swimmers (or coaches) who would be interested enough to use them, but didn't previously know enough to do so.
Plus, even if you're not the type to be interested in quantifying your training, it can be useful to think about workouts in this general framework.
And, at the very least, this might serve as a place to discuss some of the details without worrying about driving those other threads too far off-topic.
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Yes, I understood that
In that case, then, you're correct. According to the models, you're still "recovering" from the workouts you did 5-10 weeks ago. But 5 time constants out, you're 99.4% recovered, so you probably don't still feel tired. :)
The model doesn't distinguish between regular training and overtraining. Recovery from both is assumed to be the same. Maybe it's just when you're overtrained that the damage is significant enough that you can still feel it many weeks out.
Avoiding overtraining is actually where I get the most real-world use out of these models. But that's a separate topic that I think I'd better save for later.
Yes, I understood that
In that case, then, you're correct. According to the models, you're still "recovering" from the workouts you did 5-10 weeks ago. But 5 time constants out, you're 99.4% recovered, so you probably don't still feel tired. :)
The model doesn't distinguish between regular training and overtraining. Recovery from both is assumed to be the same. Maybe it's just when you're overtrained that the damage is significant enough that you can still feel it many weeks out.
Avoiding overtraining is actually where I get the most real-world use out of these models. But that's a separate topic that I think I'd better save for later.
