Sports Data Visualization And Data Analysis

Big data analysis is revolutionizing professional sports,influencing everything from game strategy and player conditioning to how fans interact with the sport.To help understand the underlying information,data visualization techniques are widely used to display data in a straightforward manner,while data analysis is used to extract hidden patterns in data.With the advent of sensor technology,basketball is now a sport with diversed data,at the same time possessing many qualities shared by other sports.Therefore,this paper uses basketball as an example to demonstrate the use of data visualization and data analysis in sports.We present a multifaceted web-based NBA data visualization system,BasketView,that enables basketball professionals to analyze the game from four perspectives: season level,game level,event level,and region level.Season level view uses a novel visualization design called BandView,where a combination of bar graph and flow graph is used to visualize win-loss statistics and game statistics simultaneously.In game level view,two visualizations,namely,PlayerStream and GameClock,are coupled together to reveal the changing contributions of all players during a basketball game,as well as all events that take place.To complement the game level view,event level view uses a dynamic visualization called CourtChart that animates the movement of on-court players and basketball.Lastly,region level view uses PlayerMap to allow basketball professionals to quickly identify talents within a country.BasketView connects all four components with interactive features,providing users an easy-to-use and comprehensive toolbox to analyze basketball games.