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How to Deal with Messi Data

Tuesday, June 9, 11 AM ET

Key Takeaways

  • Learn how data is used in soccer analytics to measure player performance.
  • Get hands-on calculating metrics using FIFA World Cup data.
  • Build practical Python skills for real-world data analysis projects.

Your Presenter(s)

Pegah Rahimian headshot

Pegah Rahimian

Soccer Analytics Researcher at Uppsala University

Pegah applies data science and machine learning to analyze soccer player performance and game strategy. Her work focuses on sports analytics, combining statistical modeling and domain expertise to generate insights for football performance and decision-making. She is active in the research community, contributing to projects at the intersection of AI and sports. Previously, Pegah studied and worked in data science and analytics, building a strong foundation in quantitative research and applied modeling.

Why this matters

Working with messy, real-world data is one of the most important skills for any data scientist—and what better dataset to explore than the performance of one of the greatest players of all time? In this session, you’ll dive into soccer analytics and learn how data is used to quantify player performance, using Python to turn raw match data into meaningful insights.

In this code-along webinar, Pegah Rahimian, a Soccer Analytics Researcher at Uppsala University, will guide you through analyzing World Cup player data with a focus on Lionel Messi. You’ll calculate key performance metrics, explore patterns in gameplay, and learn how to structure your analysis using Python. This session is perfect for data scientists and soccer fans who want to sharpen their skills on a fun, real-world dataset.

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