Comparative study of football team rating system using elo rating and pi-rating for Switzerland Super League

Sukarno, Siti Nurzulaika and Saringat, Mohd Zainuri and Mustapha, Aida and Razali, Nazim (2021) Comparative study of football team rating system using elo rating and pi-rating for Switzerland Super League. Penerbit UTHM, UTHM.

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A sports rating system is a system that analyses the results of sports competitions to provide ratings for each team or player. Usually, in a football match, the audience will predict which team will win based on the goals scored by the team at half-time or penalty. This prediction is important because when evaluating match results, it is important to first compare the potential strength of the teams involved in the match. Due to this, the main goal of this research is to compare the performance of the team rating system using Elo Rating and Pi Rating when forecasting match outcomes in association football. The well-known Elo Rating system is used to calculate team ratings, whereas a Pi Rating is used to predict the football match results based on a team’s performance to win the match when playing home or when playing away. Two different techniques are used to generate forecasts. Both types of models can be used to generate pre-game forecasts. The Elo ratings worked better when predicting matches from a large data set. The Pi Rating system applies to any other sport where the score is considered as a good indicator for prediction purposes, as well as determining the relative performances between adversaries. Data used in this study focuses on the dataset football match by Switzerland Super League. The dataset from the website is a dataset composed of around 1421 data of matches of the Switzerland Super League. The research figures out the classification model based on the Decision Forest classifier is an effective classifier with 68% f-measure for Pi Rating and 73% for f�measure Elo Rating. Therefore, Elo Rating is the best team rating system to predict football competitions.

Item Type: Other
Uncontrolled Keywords: Football rating; team rating system; elo rating; pi rating; prediction
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Mr. Abdul Rahim Mat Radzuan
Date Deposited: 15 Mar 2022 02:32
Last Modified: 15 Mar 2022 02:32

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