Training load monitoring

On August 26th, Hexfit welcomed Aurélien Broussal-Derval and David Pellier (Delta Performance) for a virtual round table discussion hosted by our faithful Etienne Dubois. The topic discussed: monitoring training loads.

Good load monitoring is a major issue for the athlete's long-term performance: fewer injuries mean more training time. It is therefore very important for the physical trainer to make the right decisions. What to follow, which tools to use, which mistakes to avoid, how to interpret the results? We summarize everything in this article.



When it comes to training loads, a lot of things are possible, a lot of new things are coming out all the time and the data sources are multiplying: the risk of being overwhelmed by data, of wasting a lot of time entering them manually or of tracking data that doesn't speak for itself is very real.

Nowadays, it is the excess of data that presents an even bigger challenge. With connected objects so much data is available that the biggest challenge is to collect it in one tool.

The fitness trainer becomes a "data scientist" and must:

  • Select the right data to track
  • Equip yourself with a tool that allows you to centralize and represent them correctly
  • Analyze them finely by adapting to the athlete and the context


  • Choose data that cannot be ignored.
  • Trust in the simplicity of the data you are tracking: the important thing is that it is sustainable!
  • Make sure that any data you collect has a purpose.
  • Don't waste time collecting data for data's sake.

At the very least, follow the RPE (calculation details: perception of effort x duration of the session). It represents the perceived effort according to the athlete's conditions on the day and gives you an evaluation of his or her feeling.



Depending on the discipline and the objective of the athlete, you can add other analyses. Here is a list (not exhaustive of course) of the most important load data:

  • RPE (perception of effort x duration of the session) over time. It represents the perceived effort according to the athlete's conditions on the day and gives you an evaluation of his feeling.
  • Compare the chronic load (weekly load which includes the last 4 weeks) and the acute load (load of the last week). This comparison will give you an idea of possible drift.

  • Monotonicity: index of the fluctuation of the daily load in the week (standard deviation of the load in the week). If it is high AND associated with a high load, it gives an idea of the overload issue.

  • Constraint: (weekly load x monotony). Allows you to see the consistency of the load that you bring. Be careful when approaching 6000 and strong alert beyond 10000.
  • Freshness index: difference between the chronic load and the acute load. Quite telling for athletes.


The monitoring tool is not trivial: what criteria should be considered to ensure the right choice?

1 - A STABLE tool  

We have all used EXCEL. As powerful as the tool is, when it comes time to analyze the training load monitoring data, merge the files... it crashes.

2 – A tool that allows professionals to SHARE

And when you have to share data between professionals, each one adds their own tools and methods to the document... which makes the data incompatible with each other and complicates the merger. We need a tool that frames the formatting and structure of the data for everyone.

3 – A tool that guarantees the PERENNITY of the data

The data must not disappear with the professional: when a physical trainer leaves a structure, the training load analysis data must remain existing and usable.

4 – A tool that allows you to obtain the data SYSTEMATICALLY

The tool should make it easy to collect the data from the athletes, in the most automatic way possible (you don't have to chase them to get it).






Depending on the athlete, your load monitoring will not be exactly the same:

  • Some athletes take comfort in data, and need it to make sure they are doing well. They will gladly fill out comprehensive questionnaires and provide reliable, systematic, and useful data.
  • Others are much more intuitive: they will never fill out a questionnaire. They won't be interested in load tracking data; it's up to you to choose the data that is truly sensitive to you, without forcing it...

And of course, you will have to adapt to their profile.



In load analysis, the raw number means nothing. It is always in relation to something else, that you can draw useful conclusions

  • The relativity of loadsKeep an OVERVIEW of each index. Relate them to each other and "read between the lines"! For example, monotony alone, if the training load is low, does not bring any particular alert.
  • The contextThe analysis of the load must be put back into the planning objectives and the time of year of the competitions.
  • DurationThe load is calculated in arbitrary units and according to free scales; based on these choices, you cannot necessarily analyze the raw data or compare two athletes at a given moment. Consider the figures in the long term, with the knowledge of the athlete, according to the loads you know he can take.
  • TrendsIt is the consistency in the evaluation of the data that is interesting: aberrant data, temporary, or confirmed drift?
  • Be alertThe challenge is to be able to cross-reference and calibrate the information to have a useful alert system. And this is where a tool like Hexfit can be particularly useful.




These data provide valuable information to adapt the programming trajectory, regulate the load with regard to a competition date, on approach cycles of 3 to 6 weeks, depending on the objective.

Even when not following a competition, the need for such markers is present. It contributes to a personalized approach, even in recreational or health sport coaching. The indicators will be different; we are not only talking about training load. A Hooper questionnaire for example can be very useful. All of this can make the intervention more professional and give meaning to the session of the day.

Adaptation of care is the key to any support.   



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Camille Boutin

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