How can be reduced the number of injuries among young soccer players?

⎫ How can be made to the professional athlete compete for more games in the season in front of the current competitive calendar?

How can be optimized the time of the technical staff members in the data tabulation of the training sessions?

How can be accessed the information from athlete quickly and objectively in the pre- and post-training by Coaches?

⎫ How can be integrated athletes and technical staff members into a single app that aims for controlling training-load?


Faced with the technical-tactical, physical and psychic demands which soccer players are currently exposed, there is a great effort on the part of sports professionals around the world in the search for answers. Our role is then to contribute to the solutions, through the development of strategies that aim to minimize the large number of injuries in sports, consensual agenda of the American College of Sports Medicine and European College of Sports Science (Meeusen et al., 2013). In order to achieve this goal, it is essential that there is a controlling training-load. Because although the cause of the injury is multifactorial, it is results from a sum of loads that generate a force that exceeds the limit supported by the biological tissue (Zernicke; Whiting, 2008).


Currently, one of the greatest challenges in relationship the risk of injury to athletes is how to carry out this controlling individually, especially in team sports.


The importance of the improvement in this process is more prominent, due to studies that point out the existence of significant relationships between the injury and the handling of the training load  (Gabbett, 2016), and even with the performance of soccer teams (Hagglund et al., 2013). An increase in training load (greater than 10% over the previous week) was associated with a 40% increase of the injury risk in Australian Football players  (Piggott et al., 2009), still lacking studies with this characteristic in the soccer. Due to a study that tracked for 11 years the relationship between injury numbers and team performance in the UEFA Champions League concluded that the teams reached the top when they suffered fewer injuries in the course of the season (Hagglund et al., 2013). In addition, this study emphasized the importance of developing injury prevention strategies so that soccer teams increase their chances of success in competitions, especially for those that occur most in the sport; such as muscular  (Ekstrand et al., 2016), and knee injuries (Yang et al., 2012).


Some data typically collected in the athletes' workout routine by questionnaires and tabulated later in Excel spreadsheets will be collected through the LOAD CONTROL®. Using the app, the volunteers send the information via smartphone to the tablet of the technical staff. Furthermore, daily and prior to the training session, athletes send subjective perceptions of quality of recovery (PQR), sleep (PQS) and muscle soreness (PMS) thus allowing the monitoring. After the session, the athlete sends his subjective ratings of perceived exertion (RPE) to determine the training load. Thus allowing the quantification with the weekly RPE being calculated in arbitrary units (AU), when the RPE is multiplied by the duration of the training session. The analyzes are performed by the weekly internal load from RPE and external load obtained by GPS with the weekly distance traveled. Athletes also periodically respond the mood scale alternatives through the app, as well as heart rate (HR), creatine kinase (CK), countermovement (CMJ) performance, and the duration of the activities carried out are entered into the app directly by the technical staff. 

Therefore, this control process of training load can be performed during the entire competitive season in order to achieve the results previously planned by the technical staff.

The information sent to the LOAD CONTROL® by the athletes and Technical Staff becomes available in the cloud and the connections are encrypted, thus guaranteeing the security of the data.

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