Istraživanje obrazaca i trendova u učinku Premier lige kroz analizu podataka

master's thesis

• Title (english): Exploring Patterns and Trends in Premier League Performance through Data Analysis
• Author: Domagoj Blažanin
• Mentor: Marina Bagić Babac (mentor)
• Committee member: Marina Bagić Babac (predsjednik povjerenstva)
• Committee member: Tomislav Kos (član povjerenstva)
• Committee member: Nikica Hlupić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-09-20, Croatia

Abstract

Ovaj diplomski rad će istražiti i analizirati obrasce i trendove u performansama Premier lige korištenjem tehnika analize podataka. Novi skup podataka o ishodima utakmica Premier lige stvorit će se korištenjem različitih javno dostupnih skupova podataka. Prvotna obrada podataka uključivat će istraživanje i vizualizaciju raznih statistika kako bi se identificirale ključne varijable koje utječu na ishod utakmice. Cilj je predvidjeti ishode Premier lige na temelju različitih numeričkih podataka, pružajući važne uvide u čimbenike koji utječu na rezultate utakmica. Nekoliko modela strojnog učenja, uključujući regresiju, stabla odlučivanja i neuronske mreže, bit će obučeno i testirano za predviđanje ishoda utakmica, što će omogućiti usporedbe između modela.

Abstract (english)

This thesis will explore and analyze patterns and trends in Premier League performance using data analysis techniques. A novel dataset on Premier League match outcomes will be created by utilizing various publicly available datasets. Data pre-processing will involve exploring and visualizing statistics to identify the key variables that influence match outcomes. The objective is to predict Premier League outcomes based on various numerical data, providing valuable insights into the factors that affect match results. Several machine learning models, including regression, decision trees, and neural networks, will be trained and tested to predict match outcomes, allowing for comparisons between models.

• Keywords: strojno učenje; klasifikacija; Premier liga; predviđanje ishoda; analiza podataka
• Keywords (english): machine learning; classification; premier league; outcome prediction; data analysis
• Language: english
• URN:NBN: urn:nbn:hr:168:688877
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2024-03-28 07:43:30