What Should You Measure to Monitor Training Load? The International Consensus Statement

Your athletes rate their fatigue every day. When did anyone last look back at that data? Collecting load data is not the goal in itself. In 2016, leading sports scientists met in Doha, Qatar, to set out both the "how" and the "why" of monitoring athlete training loads. This paper is the resulting consensus statement, and its core idea is simple: look at load from two sides — what athletes did, and how their bodies responded.

What the study looked at

This is not an experiment but an international consensus statement. In February 2016, experts gathered in Doha for the meeting "Monitoring Athlete Training Loads – The Hows and the Whys" to share research evidence and applied practice.

The statement brings that discussion together into a single framework for coaches and sports science and medicine staff.

Key findings

• Load has two dimensions
  • External load: what athletes did — distance covered, weight lifted, training time
  • Internal load: how the body responded — perceived exertion, heart rate
• Three questions in one framework: what load monitoring is and how it is used, why it matters (purpose and evidence), and where the field is heading
• Data collection and interpretation need structure: with rapid growth in monitoring technology and research, the field needs clarity not only on how to measure but on how to interpret and use the data

How to read this in practice

• You do not need to measure everything at once. Start by recording what was done in training alongside how hard athletes found it
• Record the same way, consistently. If methods change, you can no longer compare over time
• Decide in advance who looks at the data, when, and what decisions it informs. Do not make collection the end goal

This is a consensus statement, not a trial comparing specific metrics. See the original paper for details on measurement methods.

Using ATHCON

With ATHCON, athletes complete a quick daily check-in on their phone — sleep, fatigue, soreness and more — and each response is compared with their own 14-day baseline and classified as great, normal, caution or alert. It is a way to collect information on how athletes respond, every day, without extra burden.

Because it sits alongside training logs (weights and reps), you can view what athletes did and how they responded together. The classification is a prompt to check in with the right athletes; the final decision always rests with the coach.

Takeaways

• Monitor load from both sides: external load (what was done) and internal load (the response)
• Decide why you are measuring and who will use the data before you start
• Consistent methods are what make changes interpretable