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Soccer Result Prediction using Data Mining through Predictive Analytics

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dc.contributor.advisor Guha, Sumanta
dc.contributor.author dasu, Ankith
dc.contributor.other Phan Minh, Dung
dc.contributor.other Anutariya, Chutiporn
dc.date.accessioned 2017-05-08T07:36:26Z
dc.date.available 2017-05-08T07:36:26Z
dc.date.issued 2017-05-08
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/855
dc.description.abstract Data mining techniques have proven to be most efficient in predicting the soccer scores. The overall aim of this research study is to take sports training and match data and extract relationships between these using data mining and machine learning techniques. Predicting the outcome of sporting events is a business which has grown in popularity in recent years. Recent times have changed the way sports are predicted. Predictions now typically consist of two distinct approaches: Situational plays and statistical based models. In this research, probabilistic analysis of the streaks of match outcomes is used. At the end of this research, the winning or losing probability of a team can be predicted. For doing so we will be needing the performance of the team i.e. the win/loss streak in its recent ‘x’ matches and the rankings of the two teams playing the match whose result is to be predicted. The team's Home field advantage is another factor which was considered to increase the accuracy of the model. Keywords: Predictive analytics, Markov Property, Data mining. en_US
dc.language.iso en en_US
dc.publisher AIT en_US
dc.subject Data Mining en_US
dc.title Soccer Result Prediction using Data Mining through Predictive Analytics en_US
dc.title.alternative AIT en_US
dc.type Research report en_US

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