A new measure in strength training

Sprinting ability is essential in most team sports such as rugby, football or basketball. But this ability does not develop in stable and controlled conditions: players are constantly subjected to changing demands, whether it is receiving, driving, passing, hitting or throwing the ball.

Traditionally, this aspect was worked on in the gym using “weights” in purely vertical conditions, but that has changed in recent years. Now, strength work adds challenges that contribute to improved adaptability, and with it performance.

However, to study the variability produced, conventional linear measures – such as acceleration – do not seem sufficient, as the information they provide about changes is very limited.

In the study of movement, what is known as entropy analysis has gained popularity in recent years, a type of non-linear measure that specifically addresses variability or the ´desorden´ of a time series. Paradoxically, it has never been used to study strength training in team sports.

A team of researchers, including Jairo Vázquez, physical trainer of F.C. Barcelona, has developed a work in which he demonstrates for the first time the capacity of entropy measures to capture variability in this type of exercise. The study is linked to a doctoral thesis carried out at the INEFC in Barcelona and is published in the Journal of Science and Medicine in Sport.

A pioneering study

“It is becoming increasingly clear that strength training should not consist merely of exercises such as squatting with a bar and weights,” says Vázquez. “It is necessary to add challenges or conditioning factors that allow an adaptation to variability, because we do not learn by constantly repeating the same solution to a movement problem, but by constantly solving a new movement problem. And a very easy challenge to introduce is the ball.

In the study, twelve professional rugby players performed a strength exercise using a rotational inertia machine, which combines a concentric and eccentric type of work and has already shown its great value.

Distributed into four different sessions over a week, the exercise consisted of a forward and backward movement in the horizontal plane to which the presence of a ball could be added.

To do this, the player had to pick up the pass that another made from the right and then throw it to a receiver on his left. “In football or rugby, the majority of movements are horizontal, movements that are not those that occur during the typical squats.

With this exercise we mixed several positive points: on the one hand, a more common type of movement in a rotational inertia machine with which we already know we get positive results.

On the other hand, the presence of the ball introduces a disturbance that stimulates adaptability to the environment. Through the use of an accelerometer, “we wanted to know how this disturbance influences and what changes it introduces”.

Three types of measurements were taken. One, the most traditional: the average acceleration and the peak (or maximum) acceleration that are based, as Vázquez explains, on the “more is better”.

Comparing the type of exercise with ball and without ball, no differences were seen in the peak acceleration, only in the average acceleration and only in the forward movement, which was greater when the ball was introduced.

The other, more novel measures consisted of the entropy analysis, which measures “the variability of the signal,” says Vazquez, since “each signal has a structure, and acceleration does not have to be regular.

In this case there were differences -or clear tendencies towards differentiation- between the exercise with and without ball, both in the forward and backward movement and in the global one. In addition, using a type of analysis that addresses multiscale, variability appeared in the wider windows, “which can be linked to movement,” says Vázquez.

According to motor learning theory, there has to be a certain level of variability – neither too big nor too small – for performance to be optimal. “It’s true that the results of the study were expected,” assumes the trainer, “but no one had previously demonstrated it. It is also confirmed that traditional measures are insufficient to capture this training variable.

An advantage and a step further

Adapting to variability not only results in increased performance, it also decreases the risk of injury. “It’s similar to the process by which a hand hits a table,” says Vázquez. “If we repeatedly move the hand over the same point, the damage is large and localized. But if there is a slight variation in the contact surface, the damage is distributed and the risk is less”.

Adaptation means a higher level of coordination, but this will reduce the variability over time and make the training less effective. “This work is a great first step to continue studying in this line and know its full applicability to training.

Now that we know that we can measure variability we have a tool to modify and adjust the exercises, to place them in the window in which we can train the adaptation,” he says. “The reduction of entropy would be the modern and equivalent sign that we have to increase the weight in the machine”.