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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/8928

Title: Dynamic bayesian forecasting models of football match outcomes
Authors: Owen, Alun
Issue Date: 2009
Publisher: © IMA
Citation: OWEN, A., 2009. Dynamic bayesian forecasting models of football match outcomes. The Institute of Mathematics and its Applications (IMA) Proceedings of the 2nd International Conference on Mathematics in Sport (IMA Sport 2009). Groningen, The Netherlands, 17-19 June 2009.
Abstract: Dynamic Generalized Linear Models (DGLMs) are essentially generalised linear models with parameters that are stochastic. They are Bayesian in flavour and are particularly suited to forecasting applications. This paper outlines a practical implementation of a Poisson DGLM model that can easily be deployed using the freely available software WinBUGS. Using match results data from the Scottish Premier League (SPL) between 2003/2004 to 2005/2006, the DGLM approach is shown to provide more improved predictive probabilities of future match outcomes, compared to the non-dynamic form of the model.
Description: This paper was presented at the 2nd International Conference on Mathematics in Sport (IMA Sport 2009), Groningen, The Netherlands,17-19 June 2009: http://old.ima.org.uk/Conferences/maths_sport/index.html
Version: Published
URI: https://dspace.lboro.ac.uk/2134/8928
Publisher Link: http://old.ima.org.uk/Conferences/maths_sport/index.html
Appears in Collections:Conference Papers (Mathematics Education Centre)

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