Introduction to Sport Analytics

The course Introduction to Sport Analytics provides an introduction to sports data science with a focus on athletics. Students will start learning how to analyze race data, clean and visualize performance trends, with the final goal of building a basic predictive model. The course covers topics such as data types in sports (performance stats, environmental data and more), data sources, data cleaning techniques, and exploratory data analysis (EDA). Later, students will explore how to use sports statistics and performance metrics, to build a basic predictive model using machine learning. Through a practical mini-project, students will apply their knowledge to real-world sports data, getting an hands-on introduction to data analysis and predictive modeling.

No strong prior experience is required, but a basic knowledge of python is strongly suggested. Also, please arrive with a python environment already set up on your laptop. A passion for sports and data science is encouraged. The course will be taught in English.

Lorenzo Galli
I’m Lorenzo Galli, a 20yo mobility student currently in my second year of Bachelor’s in Informatics at USI. I’m originally from the University of Pisa. I’ve been passionate about track & field for nearly 15 years, and my interest in Informatics motivated me to bring together sports and technology. I’m particularly fascinated about data science and how can we use sports data to predict different scenarios, such as winning times, results, injury prevention and more. In 2024, I developed Wind Correction, an iOS app that adjusts athlete times based on wind conditions. Although I’m still a student, I believe teaching is the best way to learn, and I would love to share my passion and knowledge with other motivated students for shared learning.

Amedeo Zappulla
My name is Amedeo Zappulla, and I am a second-year Bachelor’s student in Computer Science at USI. Over the past four years, I have built my skills through competitive programming, a passion that has driven me to excel and ultimately earn a full scholarship here at USI.
In the previous semester, I had the opportunity to work as a teaching assistant for the Computer Architecture course. This experience deepened my appreciation for teaching and motivated me to seek further opportunities to refine my skills in this area. Beyond academics, I have always been eager to apply my knowledge to real-world challenges. I see data science as one of the most impactful fields where I can leverage my problem-solving abilities to drive meaningful insights and innovation.