CANCELLED: Soccer Analytics Using Machine Learning

Music City Center 

This course offers a comprehensive introduction to soccer analytics and machine learning, focusing on how data science is transforming the sport. Participants will begin by exploring the historical context and current applications of soccer analytics, followed by hands-on sessions on Python programming essentials, including data manipulation with Pandas and visualization techniques using Matplotlib and Seaborn.

Key machine learning concepts, such as classification, logistic regression, tree-based models, and deep learning, will be covered with a focus on soccer-specific applications. The course also delves into regression models, including Poisson regression for predicting match scores, and explores the role of feature engineering in enhancing model performance.
In addition, participants will gain insights into sports betting strategies, integrating machine learning models for risk assessment and decision-making. The course is structured to balance theory with practical applications, offering participants an opportunity to work with real-world soccer datasets.

By the end of the course, attendees will have a solid foundation in using machine learning to analyze soccer data and make informed predictions, equipping them with valuable skills for both academia and industry.

Section on Statistics in Sports