How to match internal and external load?

In the graph below, we have included heart rate, LPS player load, and N11 player load for one single player. We have normalized the intensity based on the maximum value registered by each of the three systems in this specific session. We tracked a training session, that started out with possession games in a small area, then moved on to possession games in a larger area, and finally a match at three quarters of a full pitch. After analyzing the data, it’s distinct how data from all players show a very close correlation between the heart rate and the load from the N11 leg sensor throughout the entire session.

From the first part, where the players made a lot of high-intensity movements over short distances to the last part, where they also had high-intensity actions over longer distances. We don’t see load from the leg sensor as a replacement of heart rate data. What we pay attention to is the close correlation between the heart rate and the N11 player load which highlights the advantages of tracking player load at the leg. By registering all leg movements no matter how fast or long the player is running, the leg sensor provides a much more accurate picture of player load than sensors at the upper-body. For some this might be a controversial statement, but to us it’s no surprise that new technology makes it possible to do things in a new and better way.  

Think about it like this: Over 80% of injuries in football occur in the legs – and many of them are caused by overload. The primary contributors to load are accelerations and decelerations of the legs. However, current tracking systems attempt to quantify these accelerations and decelerations using sensors placed on the upper body. This approach seems fundamentally illogical and we believe it’s time to re-engineer how to track player load.

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