Discovering associations between players' performance indicators and matches' results in the European Soccer Leagues

DOI10.1080/02664763.2020.1772210OpenAlexW3030515235MaRDI QIDQ5861602

Silvia Golia, Maurizio Carpita

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1772210

zbMATH Keywords

Bayesian networksnaive BayesElo ratingKaggle European Soccer databaseoverall performance indicators

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items (1)

Observed heterogeneity in players' football performance analysis using PLS-PM

Uses Software

• bnlearn

Cites Work

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• Bayesian network classifiers
• Guest editorial: Special issue on machine learning for soccer
• Learning Bayesian networks: The combination of knowledge and statistical data
• Training and assessing classification rules with imbalanced data
• Bayesian modelling of football outcomes: using the Skellam's distribution for the goal difference
• Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
• Using machine learning to draw inferences from pass location data in soccer
• Predicting the future performance of soccer players
• Combining historical data and bookmakers’ odds in modelling football scores
• Testing and ranking on round-robin design for data sport analytics with application to basketball
• Exploring and modelling team performances of the Kaggle European Soccer database

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