Background. Data from training sessions is gathered by a trainer from the playerswith the goal of analyzing and getting an overview of how the team is performing.The collected data is represented in tabular form, and over time the effort to inter-pret it becomes more demanding.

Objectives. This thesis’ goal is to find out if there is a solution where collecting,processing and representing training data from football players can ease and improvethe trainer’s analysis of the team.

Methods. A dataset is received from a football trainer, and it contains informa-tion about training sessions for his team of football players. The dataset is used tofind a suitable method and visualize the data. Feedback from the trainer is used todetermine what works and what does not. Furthermore, a survey with examples ofvisualization is given to the players and the trainer to get an understanding of howthe selected charts are interpreted.

Results. Representing the attributes of most importance from received datasetrequires a chain of views (usage flow) to be introduced, from primary view to qua-ternary view. Each step in the chain tightens the level of details represented. Boxplot proved to be an appropriate choice to provide an overview of the team’s trainingdata.

Conclusions. Visualizing training data gives a significant advantage to the trainerregarding team analysis. With box plotting will the trainer get an overview of theteam and can hereafter dig into more detailed data while interacting with the charts