- The main goal of the center is to gain new and fundamental insights into what affects the performance and overall health of female elite football players, says department leader of Holistic Systems, Pål Halvorsen.
- A general objective is to devise novel methodologies for epidemiological research that might impact research fields in both sports and medicine. In particular, we aim to develop non-invasive, privacy-preserving technology that enables us to continuously quantify and monitor athlete behavior where we derive analytic insights from different perspectives (e.g., biomechanics, sports-specific science, medicine, coaches, and athletes).
In the current gold standards for epidemiology, observational prospective cohort studies include that cohort subjects are followed in detail over a longer period. This is an error-prone and tedious task that has for a long time been carried out using pen and paper, and later doing a manual, tedious analysis. Making this entire process easier is the main responsibility of the researchers from SimulaMet.
- We aim for quantification and accurate analysis technologies that enable a personalized assessment and performance development of elite athletes. Together with UiT and Forzasys AS, we have earlier developed and used an automatic performance monitoring system for athletes used by both national and elite series soccer teams, says Halvorsen.
Responsible for data collection and storage
The automatic performance monitoring system collects athletes’ subjective parameters, like training load, wellness, injury, and illness, using a small questionnaire-app running on their mobile phones, and the data is transferred to a cloud-based backend system. Then, from a trainer-portal, the data can be automatically visualized for both individual players and team overviews.
Pål Halvorsen leads the first research task for data collection and storage, which is closely related to the analytics research task.
- In FFC, our objective is to extend the system further to include female-specific parameters and introduce more automatic analysis using, for example, machine learning. We will host and develop the system for all the teams participating in the project, and we will initiate automatic analyses that might be able to predict future overuse injuries or to help maybe to find the best development process of a player or a team.
Hundreds of active female football players are participating
Svein Arne Pettersen (head of research at the School of sports sciences, UiT) is the center leader, and he has collaborated with the researchers at SimulaMet for a long time.
- In general, the center will develop and apply computer science, mathematical and statistical methods, and technologies to solve problems in sciences related to the performance development of female elite football athletes. The primary user cohort includes all active players and coaching staff, and leaders in the top Norwegian national league, as well as the for many years best Danish female elite team Fortuna Hjørring. Another local cohort of female athletes in Tromsø will also be included, and we have a strong intention to include other European elite clubs. In total, there will be several hundred players participating in the project, says Pettersen.
But why this focus on female athletes?
Svein Arne explains that gender-specific aspects of sports including football, have earlier received little focused attention from the international research community, where the vast majority of scientific studies have been performed on male players.
- Thus, to contribute to the body of knowledge regarding women’s training and game, and help practitioners make more informed decisions, more research is needed on females in relation to each training principle and the demands of the game by position. Also, hormonal differences between men and women might play a role in adaptation to training stimulus, and recovery after training, he says.
More efficient and professional training and game management
The response from the clubs is initially positive at this early stage of the project. For example, the two top teams in Toppserien both use the systems provided. In Rosenborg BK, they use both GPS player tracking system and the automatic performance monitoring system, and according to Gunnvor Halmøy (physical trainer and medical coordinator for both RBK-kvinner and the Norwegian National team for women), the provided technical solutions have had a positive effect in making the everyday training and game management more efficient and professional.
The project started in January 2020, but there has been a slow start due to the Corona pandemic delaying all sports activities in Norway (and the rest of Europe). Still, various teams have monitored their players, and data keeps coming in. Thus, there are no female-specific data analyses performed yet. However, using earlier data from male elite teams, there have been performed initial experiments analyzing data using machine learning, and it seems like the technology to a certain degree can predict future performance-related parameters.