I like to think about classifying athletes in sport science research along a 3-dimesional model that considers (1) Fitness, (2) Performance, and (3) Training status
We recently published an article comparing the NIRS-derived deoxy-BP to the RCP (VT2) in a ramp cycling test. I want to use this and another similar study to understand the important differences between threshold measurements, the natural variability in measuring physiology, and how understanding this variability can help us prescribe training targets that will elicit the desired training stimulus for ourselves and our athletes.
This is a basic template for what I currently consider to be a solid, simple, sustainable training plan that can be individualised, modified, mixed around, and repeated near ad infinitum. This can be used as a foundation for whatever training goals we have, be they focused on performance with a specific peak event/race date in mind, or more about sustaining general health, fitness, longevity, and resiliency.
Our hypothesis is that the linear extrapolation of PS SmO2 during the work stage can predict time to exhaustion, when performed to task intolerance. Across both male and female subjects, we have seen that in 27 of 36 trials, both the vastus lateralis and paraspinals oxygenation slopes provide a reasonable prediction of TTE.
The next generation approach to metabolic profiling and training prescription will almost certainly not include breakpoints or thresholds at all, and will use more flexible methods of describing continuous physiological response profiles in real-time. I think that by defining the rules which our brains are already using to find patterns, we will be able to better understand the real physiological relationships for an individual athlete, and improve how we can apply insights to that individual athlete's training.