• Predicting the win probability using logistic regression for top four English Premier League teams

    Author(s):
    Aladár Kollár (see profile)
    Date:
    2021
    Subject(s):
    Sports--Information services
    Item Type:
    Article
    Tag(s):
    football, prediction, sport betting, Sport informatics
    Permanent URL:
    http://dx.doi.org/10.17613/mme4-6a39
    Abstract:
    Predicting the outcomes of football competitions has long piqued the attention of the general public as well as bookmakers. A combination of algorithm,ranking criteria and scoring scales can be used to decide the outcome of a game. The English Premier League(EPL) is the most famous and watched football league in the world. Thisresearch seeks to examine the factors that can affect the winning-probability of top four teams in the running season, 2020-2021. They are Manchester city, Manchesterunited, Leicester city and Chelsea. The match results data have been collected from these four teams for 105 matches in EPL. This includes the 30 matches of current season, 38 matches of season 2019-2020, and 38 matches of the season 2018-2019. The data are analyzed using the logistic regression implementing the glm()function of ISLR package in R. The main findings of this study suggest that the probability of winning a match by Manchester City increases if there are direct free kicks, defending set pieces, creating chances, and attacking down the wing increases. In case of Manchester united, the win-probability increases if longshot, counter attacks increase. The wining probability of Manchester united decreases if its offside increases. In case of Leicester city, the winning probability deceases if the opposite team make counter attacks. For the team Chelsea, the free kick shooting increases the winning probability. The Chelsea, however, can make the winning probability decreases by making individual errors.
    Notes:
    Aladár Kollár’s research area includes: sports tips, forecasts, and data analysis for sport betting. Budapest University of Technology and Economics Author at https://mightytips.hu/ https://mightytips.hu/szerzo/aladar-kollar/
    Metadata:
    xml
    Status:
    Published
    Last Updated:
    3 years ago
    License:
    Attribution
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