Predictive Modelling for Football Analytics

Predictive Modelling for Football Analytics

Decode the beautiful game through the power of advanced statistical science. Predictive Modelling for Football Analytics provides a definitive, high-level roadmap to the data-driven revolution in sports. Learn how to transform match statistics into actionable insights, utilizing cutting-edge Bayesian methods and machine learning to predict outcomes, evaluate player performance, and gain a competitive edge in the modern football landscape.

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What You Will Learn:

Statistical Foundations: Master the core probability distributions and regression models specifically tailored for analyzing low-scoring sports like football.

Match Outcome Prediction: Step-by-step guidance on building predictive models for match results, scorelines, and dynamic "in-play" event forecasting.

Advanced Metrics & Ranking: Discover how to implement ELO ratings, Expected Goals (xG), and advanced player-ranking systems to quantify performance beyond the scoreboard.

Practical Implementation: Learn how to utilize R and Python to process large-scale match data, ensuring your models are both technically rigorous and practically applicable.

Who This Book is For: This advanced analytical guide is essential for data scientists, professional sports analysts, and football enthusiasts with a quantitative background. It is a vital resource for anyone looking to bridge the gap between passion for the pitch and the technical precision of professional predictive modeling.

Product Details:

Format: Digital PDF Download

Authors: Leonardo Egidi; Dimitris Karlis; Ioannis Ntzoufras

Publisher: CRC Press LLC

Edition: 1st Edition

Publication Date: November 7, 2025

ISBN-13: 9781032030630

ISBN-10: 1032030631