In football, for performance and training analysis, the player's position on the pitch or the number of passes/shots can only be automated and georeferenced by expensive image-based technology. Since these systems are associated with enormous costs and a special infrastructure, such football analyses can only be carried out by professional teams. However, there is a great need for inexpensive and easy-to-use smart sports gadgets for amateur teams or hobby athletes that can be used to analyze their own performance.
The goal is to develop a GNSS-supported smart shin guard (-pair), which can be used with GNSS and IMU sensors for a football specific performance analysis. The project is to be prototypically developed into an applicable system in order to be able to test the effects of data generation, data transmission, data analysis, data application in training and game operation. The planned prototypes will be equipped with modern low-energy transmission technology in order to maximize battery life. Robust georeferencing is essential for this project. If gaps in the position solution occur due to shadowing or signal failures during, e.g., duels or tackles and certain game situations cannot be captured, the meaningfulness of the product is questioned and therefore the product cannot exploit its market potential. Accordingly, a robust positioning solution will be developed in this project with the help of Multi-GNSS and Multi-Receivers (pairwise application of shin guards). With the help of a mobile analysis application, the collected data can be evaluated according to sports scientific aspects and statistically recorded. Special emphasis is put on an intuitive user interface so that the test persons can concentrate on the analyzed training data. This allows the performance of a player to be evaluated after the training or game and compared with the community through social networks to inspire performance and increase motivation.
The sport scientific questions mainly concern the assignment of measured parameters to individual performance markers, which are examined with regard to their reproducibility. Training and game will be analyzed with respect to individual markers of workload. Specifically, the analysis of game related data, which are difficult to record only with great effort, serve as the basis for subsequent training and game relevant planning and decision-making. The analysis allows choosing proper drills and routines, methods as well as the prescription of workloads but also planning single and team relevant decisions.
The SMASH project with its project partners and supporting companies (LOIs) has an ideal structure to achieve the project goals. Finally, specific recommendations for future implementation in kind of a business plan are drawn up together with the marketing specialists.