Physical Benchmark: Keuken Kampioen Divisie & Tweede Divisie
In this blog we describe a physical benchmark Kitchen Champion Division and Second Division amateur teams based on GPS player data
Trainers and coaches are balancing the training load on a daily basis. High training loads improve physical fitness and decrease the risk of injury. On the other hand, when the training load is too high this increases the risk of injury. Having to deal with these contrary consequences of high workloads makes it a constant balance act for trainers and coaches to find the optimal workload. As we have seen in the blog of last week, Raymond Verheijen’s block periodization does not give any information on where the boundary is. Fortunately, Tim Gabbett has proposed a theory on how to determine the optimal workload for your team! In today’s blog, we will, therefore, discuss his A/C Ratio model.
To get more insight into the balancing act of trainers and coaches, it is useful to see when injuries mostly occur. Injuries mostly occur when the physical demands placed on the players outweigh the body’s ability to cope with them1. Or in Gabbett’s words: when the load placed on the athlete is higher than what he/she has been prepared to handle, this increases the risk of injury. This means that we will look at load in relative terms rather than absolute terms: running 20km cannot inform you whether an injury is going to occur. Whether the person who ran 20km performed runs in the previous weeks or did not run at all is going to give you more information on the likelihood of an injury.
Now the question remains: how do we measure this in practice? Here, the terms acute load and chronic load come into play. The load the body is exposed to is referred to as the ‘acute load’ (defined as the average load of the last 7 days). The load that the athlete has been prepared for is referred to as the ‘chronic load’ (defined as the average load of the last 28 days). If we calculate the ratio between these two, called the AC-ratio, we can check whether our players are exposed to more load than they are prepared for. And thus we can determine whether they have an increased risk of injury.
Does this mean that the acute load may never be higher than the chronic load? No! Improving the physical fitness of the players requires that you expose them to more load than they are used to, otherwise no training effect will occur. So we actually encourage you to always strive for a higher acute load than the chronic load. However, if the acute load is 50% higher than the chronic load, this increases the risk of injuries2. Do you want to improve the physical fitness of your players? Aim for an acute load which is 30% higher than your chronic load2. This way, you gradually increase the physical fitness of your players without increasing the risk of injury!
There is one last aspect that increases the risk of injury: not being exposed to enough load. If the player is not exposed to enough load, detraining effects will occur. In turn, physical fitness will decrease, making the players less prepared to cope with higher workloads. To prevent detraining effects, the acute load should not be lower than 80% of the chronic load.
Using the thresholds explained above, we can create the ‘sweet spot’: the most optimal workload for your team (see image)! Even though this sweet spot is a very useful way to determine the optimal load for your team, there are also pitfalls in this theory. The theory does not give any guidelines on how to reach the right acute load. Which exercises do I need to practice? With which work/rest balance do I do the exercises? Do I need to perform short or long sprints to reach the optimal sprint meters for my team? Therefore, this theory is a good way to determine the optimal load for the players of your team, however, it is hard to precisely plan which exercises you need to do to improve performance.
The other limitation of this theory is that, unfortunately, the thresholds (A/C Ratio between 0.8 and 1.5) are no magic numbers. This means that when a player has an A/C Ratio of 1.2 this does not automatically mean that no injury will occur (would have made everything a lot easier though). The other way around, an A/C Ratio of 1.6 does not hold that the player will get an injury for sure. The thresholds are just guidelines and can be used to support your decision to change the training load. Do you see that a player is experiencing the training as harder (i.g. with RPE-forms)? Or is the movement quality getting worse? These factors, together with A/C Ratio, might as well support your decision to adjust the training load. The whole is always greater than the sum of its parts!
By comparing the load players are exposed to (acute load), to the load that the players are prepared for to handle (chronic load), the theory of Gabbett is a very practical tool to determine the optimal load. However, this theory does not give recommendations on which exercises to play to reach the optimal load. Furthermore, the thresholds are no magic numbers and should therefore only be used as guidelines.