Moroney, Karl Ryan (2014) Predicting match outcomes through game events: (Formerly: Comeback Kings: An analysis of football scores and resilient teams). Diploma thesis, Dublin, National College of Ireland.
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The purpose of this project is to analyse football scores from football-data.co.uk and investigate if match facts, such as fouls, goals, shots on target etc can predict match outcomes. The aim is to further develop the skills obtained during the course, such as databases, programming, statistics, Business Analysis and Data Mining.
The analysis was conducted through the construction of an SQL database, statistical analysis in R and machine learning in WEKA. A number of techniques were applied to conduct statistical analysis, these included: measurements of averages, normality tests, non-parametric tests and regression. Prior to conducting analysis, a comprehensive literature review was researched and completed to gain greater insight into data analytics in this field.
The results of the project proved that teams who play at home benefit from more favourable match stats, they scored higher averages of goals and are awarded less fouls against them.
The study sought to prove that there are relationships between fouls, shots on goal etc and that the outcome of the game can be predicted by match facts.
The results of statistical analyses proved inconclusive in R and, despite this, the attributes were used to complete machine learning tasks in WEKA - they did not reach the desired level of performance.
|Item Type:||Thesis (Diploma)|
|Subjects:||Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
|Divisions:||School of Computing > Higher Diploma in Science in Data Analytics|
|Depositing User:||CAOIMHE NI MHAICIN|
|Date Deposited:||15 Dec 2014 13:33|
|Last Modified:||15 Dec 2014 13:34|
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