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.
The normal assumption is that these time constants are fairly transferable. You can (some have) fit the time constants, but it requires a lot of data and work.
It's fairly reasonable to think that they should be constant. They have a fairly biological interpretation, and are related to the rates at which your body can build new mitochondria, or hemoglobin, etc. It seems reasonable to think that these biological rates would be pretty similar across individuals.
I have to disagree with these statements emphatically. As shown in the Avalos and Hellard paper, the time constants are not the same from one person to the next. Even viewed in the most harsh light given the spread of parameter estimates in the Avalos paper, three out of nine people had estimates that did not cross over.
Estimates in published work on weight lifters, throwers, runners bikes and swimmers all have given different time constants. To boot, the ratios of K1 to K2 for these models is always reported to "ONE" significant digit. Leading an observer to believe that the mathematical solutions are highly constrained. If the solutions were not so unconstrained, it is my opinion that the results would be even more widely diverging.
In addition there is published work on multisport athletes showing that individual athletes have different time constants and gain values for the different sports. Lastly, those of us who have been using these models for multisport athletes see wide variation in the time constant from one sport to the next.
As for fitting the models, it's not as hard as it might seem, the weekly or bi weekly performance test is the biggest hurdle in my opinion. Once you have that and model inputs, a little work in excel can get you where you need to go.
The normal assumption is that these time constants are fairly transferable. You can (some have) fit the time constants, but it requires a lot of data and work.
It's fairly reasonable to think that they should be constant. They have a fairly biological interpretation, and are related to the rates at which your body can build new mitochondria, or hemoglobin, etc. It seems reasonable to think that these biological rates would be pretty similar across individuals.
I have to disagree with these statements emphatically. As shown in the Avalos and Hellard paper, the time constants are not the same from one person to the next. Even viewed in the most harsh light given the spread of parameter estimates in the Avalos paper, three out of nine people had estimates that did not cross over.
Estimates in published work on weight lifters, throwers, runners bikes and swimmers all have given different time constants. To boot, the ratios of K1 to K2 for these models is always reported to "ONE" significant digit. Leading an observer to believe that the mathematical solutions are highly constrained. If the solutions were not so unconstrained, it is my opinion that the results would be even more widely diverging.
In addition there is published work on multisport athletes showing that individual athletes have different time constants and gain values for the different sports. Lastly, those of us who have been using these models for multisport athletes see wide variation in the time constant from one sport to the next.
As for fitting the models, it's not as hard as it might seem, the weekly or bi weekly performance test is the biggest hurdle in my opinion. Once you have that and model inputs, a little work in excel can get you where you need to go.
