Training Load Analysis
User guide index: https://marcoaltini.substack.com/p/hrv4training-pro-user-guide
In the training load analysis, you can first pick the metric most representative of your training. This can be RPE, TSS, Relative Effort, training distance or time, etc. - depending on your sport and the way you train. For running, I often use simply distance or time. Once you have picked a metric, you can analyze fitness and fatigue, determined as chronic and acute training loads, as well as readiness to perform and injury risk.
Chronic training load represents the overall load your body is used to taking. In general, you can see chronic load as a proxy to fitness level: the more training your body can take, the fitter you are. However, the chronic load is particularly useful when analyzing it in the context of freshness and injury risk, more than as a marker of fitness. To do so, we need to look at what happens in the short term, or your acute training load.
The acute training load represents your training load in the past week, so how much training you have recently got done. In particular, acute training load relates to fatigue: increasing the frequency of intense training in the past few days results in higher fatigue.
In the top panel, we show two percentages to provide more intuitive meanings to the current acute and chronic load. In particular, acute training load is expressed as a percentage of chronic training load, so you can see how much you have been training in the past week, with respect to the past month and a half. This way you can easily keep an eye on relative increases in load and make sure you don't overdo it. We also show chronic load as a percentage which indicates today's chronic load with respect to the maximum in the selected time period. This number might change depending on how much data you display, as a longer period of time might include past data with a higher chronic load.
Below this overview, you can find the actual data:
The difference between your fitness and fatigue can be used to determine readiness to perform. An optimal value is typically a bit above zero. This is what you can see in the freshness plot:
The ratio between your fitness and fatigue can instead be used to determine injury risk. High acute training load and low chronic training load are signs of increased injury risk, as intuitively we are loading the body more than it is used to.
Finally, we also report training monotony. Monotony refers to the similarity of daily training. In general, low monotony (a value below 1.5) is preferable so that different training adaptations can be triggered while allowing for sufficient recovery. A high value for Monotony indicates that the training program might be ineffective and lead to stagnation, or lack of improvement. Low monotony is normally associated to periodization methods alternating high and low-intensity workouts.
Both freshness and injury risk are averaged over the past week, to provide you with a single indication of the current relationship between chronic and acute load, and a simple message that will help make adjustments aiming at optimizing physical condition and avoiding injuries (see Weekly Overview).
I hope you’ll like the new Training Load Analysis page and the improvements we implemented.
Please feel free to comment below in case of any questions or feature requests.
Thank you for your support.
Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.
He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
Twitter: @altini_marco
