no23,
good points, but many clarifications are needed. What is the technology you are referring to? (you made some examples, but then I missed the point, my fault, probably).
If you don’t define that, we are talking for nothing. Omegawave? ARP? An algorithm for the analysis of data would be technology (it is)?
The main problem is with the interpretation of data, as you said, because it requires a framework. In absence of framework, we are in a similar cul de sac as that currently faced by scientists working on the interface genome/medicine. Lots, tons of data, but many problems in the interpreation.
Now, as I wrote before, we don’t still understand a lot of things (and we won’t for a lot time) and therefore the implementation of technology is not automatic. If, let’s say, such a reliable algorithm were available, its simple implementation for determining training loads, emphasis and so on would be straightforward. If a reliable and 100% effective “cure” for, let’s say, overtraining were there, its application would be as straigthforward as the application of Quinine for malaria.
Talking about expertise vs technology without a context is naive.
Said that, Charlie was a great expert.