Project: Finding "Memphis" : a rating-based player comparison visualisation
Description
With the development of sensor and camera tracking systems, it becomes easier to track player events in a football match. With these match events, post-match analysis on players can be conducted to compare the performance of players.
Comparing football players is not an easy task, there are many attributes to be covered. Typical attributes are player positions and statistics. For instance, common statistics are number of goals, number of assists, etcetera. There are many tools that can compare football players by listing all the statistics side by side for all players. Imagine we want to compare 10 different statistics for over 500 players simultaneously, and we also want to find out the 10 best players. Or sometimes, the user may want to find players that are similar to a target player, for instance, Memphis Depay. Simply listing the statistics is not the solution to such problems. To solve such problems, we designed a prototype visualization tool, called PureSoccerFX.
In our tool, we give the user the flexibility to define the key attributes of interest by introducing a so called interactive weighted attribute tree. This tree allows the user to create abstraction levels from real statistics and interactively build their own rating system by manipulating the hierarchical weighted attribute tree. With this tree, each player will get a rating and the user can simply compare this rating to find top players. We also apply a modified strip treemap to visualize the rating of these players based on the weighted attribute tree, which provides the user with an overview of all players in the league. To help the user find similar players, We designed a
player similarity graph that can compare player similarity and rating simultaneously. At last, we designed a player comparison view for the user to easily compare players from different attributes and make the final conclusion on who are the most wanted players.
Details
- Student
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YWYujie Wang
- Supervisor
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Huub van de Wetering
- Link
- Thesis