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A Bayesian approach to predict the number of soccer goals: Modeling with Bayesian Negative Binomial regression
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis focuses on a well-known topic in sports betting, predicting the number of goals in soccer games.The data set used comes from the top English soccer league: Premier League, and consists of games played in the seasons 2015/16 to 2017/18.This thesis approaches the prediction with the auxiliary support of the odds from the betting exchange Betfair. The purpose is to find a model that can create an accurate goal distribution. %The other purpose is to investigate whether Negative binomial distribution regressionThe methods used are Bayesian Negative Binomial regression and Bayesian Poisson regression. The results conclude that the Poisson regression is the better model because of the presence of underdispersion.We argue that the methods can be used to compare different sportsbooks accuracies, and may help creating better models.

Place, publisher, year, edition, pages
2018. , p. 36
Keywords [en]
Bayesian regression, Negative Binomial regression, Poisson regression, Soccer goals, odds
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-149028ISRN: LIU-IDA/STAT-G--18/006--SEOAI: oai:DiVA.org:liu-149028DiVA, id: diva2:1223567
Subject / course
Statistics
Supervisors
Examiners
Available from: 2018-06-26 Created: 2018-06-25 Last updated: 2018-06-26Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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