Two weeks ago we spoke about objectivity and how using objective measurements is often helpful in establishing a clear and unbiased picture of what is occurring. But what happens when the objective data doesn’t provide the full picture? 

A recent article by Lluc Montull, along with one of our favourite researchers in this area John Kiely looked at the monitoring of human performance through the lens of complex Adaptive systems. Many of our readers will have seen our discussions about complex adaptive systems and the difficulties that exist around understanding why a certain behaviour emerges from such a system. And the example that we have used before to demonstrate this is the performance of two individuals completing the same training program for the same activity and achieving completely different results. If we take triathletes for example they may train together and complete the exact training sessions only for one to win and the other to finish dismally.Moreover the one who wins may report feeling great and the loser feeling terrible when it comes to the affect of a particular training program. What the article highlights is the difficulty with monitoring training and performance in these environments by using objective data only. And whilst this may seem contrary to the article from a few weeks ago, you will see that in this situation not only can subjective data become objective, it is extremely important to use all forms of information gathering to integrate a system of monitoring that encompasses the complex nature of human performance. 

We have discussed in articles on complex systems and predictive coding that as complex systems humans do not always behave in accordance with objective reality. And this is the same when we measure objective reality. That is to say whilst it is important to understand with objectivity measure of an athletes capability such as VO2max, strength, power etc. These are but tools for which they can call upon. And in the complex ecosystem of performance these features interact along with the perception of the athlete to create an emergent behaviour. That emergent behaviour is typically the performance that we see. And it is the interaction between the objective measures of system features along with the thoughts, ideas and perceptions that will lead to what the person communicates (their subjective reality). And we have all seen athletes that have all of the tools, but when we speak to them, they feel as though they are not prepared, and thus perform accordingly.  

So if this is the case how do we use monitoring when it is subjective?

It appears the key is to integrate the pieces of information that you can gather and collate this to form an understanding of what that individual needs. As an example the subjective assessment of the individual about how session difficulty (RPE for example) along with objective measures of distance covered, time ran or external conditions should be combined with the result to give a stronger indication of what this athlete requires at this time for further progression. A further key point here is the adoption of monitoring trends of both subjective and objective data. When you collect subjective data regularly and record this accurately there exists the opportunity to turn this information into objective points of information. And when you combine this with the objective information such as training loads, times or outcomes, you are likely to see how that individual responds to such stimuli. 

It is a great article and we encourage you to read it. What it provides is a discussion that highlights as always that things are not as simple as they may seem, and it is our job as professionals to use every form of information that we can gather, track it and follow the trends to determine how they are responding, rather than taking the measure of one item alone (even if measured objectively accurately) and believing this represents the performance of an athlete.