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dc.contributor.authorPerez, Alejandro
dc.date.accessioned2013-02-11T12:27:37Z
dc.date.available2013-02-11T12:27:37Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10369/3838
dc.description.abstractPurpose: The purpose of this study will be to successfully predict results based on specific variables. Using the Rugby World Cup 2011 as a comparison tool, the study will determine which linear regression models are more accurate. It will then be able to determine which teams are performing above their predicted ability, and which teams are inconsistent with their form. Method: Data collected over the past five years will provide over 470 data points from which various linear regression models will be created to predict on the outcome of the games in the Rugby World Cup 2011. Results: The different types of regression models create varying levels of accuracy in the predictions, with the most accurate model providing 89.58% of correct outcomes. This provides information that determines that teams like Fiji are underperforming greatly, while Wales are scoring +15 points a game more than expected. Conclusion: Predictive models should be created using a large number of data points, and the number of variables should increase to improve accuracy in predictions. The models themselves can be used to determine how well teams performed in a tournament.en_GB
dc.formatThesisen
dc.languageEnglishen
dc.publisherUniversity of Wales Institute Cardiffen_GB
dc.titleA COMPARISON OF PREDICTIVE MODELS AND HOW EFFECTIVELY THEY PREDICT FORM BASED ON THE 2011 RUGBY WORLD CUPen_GB
dc.typeThesis


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