The aim of this thesis is to analyse, compile, and compare a set of football visualization and animation in different methods. The main part of the content establishes a systematic concept for all the football visualization charts, diagrams, statistic graphs, and animations. Spatial and attribute information of football datasets including positions, tracking, and tactical statistics is briefly introduced. The essential steps of visualizing football data through different technologies are described and important findings are shared. Then, the efficient workflow of football animations based on different technologies (e.g. Python, R, HTML5) is explained in detail, as well as evaluates the solutions of Tableau, ArcGIS, Adobe After Effects, and QGIS. Finally, the tactical, valuable, and understandable information to football coaches and players, delivered by Geovisualisation context, are interpreted and discussed.The aim of this thesis is to analyse, compile, and compare a set of football visualization and animation in different methods. The main part of the content establishes a systematic concept for all the football visualization charts, diagrams, statistic graphs, and animations. Spatial and attribute information of football datasets including positions, tracking, and tactical statistics is briefly introduced. The essential steps of visualizing football data through different technologies are described and important findings are shared. Then, the efficient workflow of football animations based on different technologies (e.g. Python, R, HTML5) is explained in detail, as well as evaluates the solutions of Tableau, ArcGIS, Adobe After Effects, and QGIS. Finally, the tactical, valuable, and understandable information to football coaches and players, delivered by Geovisualisation context, are interpreted and discussed.