In part II of this series, we saw how the time intervals between consecutive training sessions should be selected in order to respect the timings of adaptation to training for the different training methods used. Today I will talk a bit about how all this relates to the scheduling of swim, bike and run training sessions.
As an example of the timings that need to be respected in order to allow for adaptation to training, I quoted a table from Olbrecht (2000). As some readers surely noticed, those recovery times are very general and specific at the same time. General because they do not account for individual variability and specific because they apply to swimming training only. If the effect of individual variability is something easy to understand, it is worth noticing that in the context of swim training, training sessions almost always have the same length (volume), with different training methods being used inside the training session (intensity). That obviously simplifies modelling adaptation to training. For example, if we wanted to build a similar recovery chart for cycling training, where training sessions have varied length, we would need to either quantify training load (volume times intensity) or introduce some sort of temporal distintion.
So if for single-sport there are differences between recovery times, if we try to approach recovery timings in this way for triathlon training, the issue quickly becomes quite complex. As we saw before, fatigue is directly connected to recovery and adaptation to training. By modelling, even if qualitatively, fatigue and recovery, we gain insight on how the athlete is adapting to training. This is where the “art” in coaching comes into play. For the experienced coach, it is relatively easy to know what to schedule based on the information he has from the athlete and his experience in knowing the various responses to the various training methods. Most coaches, either consciously or unconsciously, model the fatigue levels of the athlete in order to prescribe training. Given the training load the coach feels is appropriate for the athlete, the training routine is set by asking the following question before scheduling the next training session: Will the athlete be able to complete and fulfill the goals of the next training session? Instead of setting in stone all the possible recovery times between all kinds of swim, bike and run workouts, a realistic accessment should be made as to the level of fatigue/recovery before each workout.
Intrinsic to this way of seeing daily training prescription, is the way we want to manipulate the athlete’s fatigue levels. Several approaches exist, most of them revolving around the concept of alternating “hard” days with “easy” days, that is to say, days where fatigue level is high with days where fatigue level is low. However, I find that the easiest model to implement is one of fairly constant fatigue levels. This will bring fairly constant recovery timings and hence very predictable responses to training, i.e. adaptations. It is obvious that one possible way of obtaining fairly constant fatigue levels, which will in turn produce predictable responses to training, is to apply fairly constant training loads. However, when scheduling triathlon training, the concept of equivalent training load between swim, bike and run is one difficult to estimate. Again that is where experience in triathlon training prescription is important for the design of the best training schedule.
During this short series, I broadly definined an approach to training prescription based on modelling the level of fatigue as a way to model recovery and adaptation to training. When talking about training, most discussions are centered around what training load should be applied to the athlete, and very seldom the characteristics of the response of the athlete to the load is mentioned. It’s as if the way the athlete handles the training sessions is not important. Modelling the athlete’s fatigue when prescribing training, even if in a qualitative way, puts the athlete back into the equation and allows us to design more effective training plans that cater to the athlete’s individual response to training.