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Title: Spatio-temporal analytics on soccer game data
Authors: Chew, Clarence Kai Wei
Keywords: Engineering::Computer science and engineering
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Chew, C. K. W. (2021). Spatio-temporal analytics on soccer game data. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: The rise of machine learning in today’s world brought about a change towards using data and artificial intelligence to improve professional football. Many teams look towards utilising such technology in order to understand their football team in a relatively new manner, giving them insightful information in the tactical aspects of footballing formations. From these data, teams are able to gain an edge over their opponent, and often this is critical in determining the match outcomes. As most technologies on football analytics are commercialized and unavailable to the public, the explores alternative ways to understand a limited set of football tracking data before converting the data into meaningful tactical information which a football team can benefit from. A web application will be developed to visualize the data with ease. The research on formation visualisation of football tracking data showed promising signs of greater understanding development towards using machine learning in the current football context.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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