
Predicting Successful Plays in Football Using Machine Learning
- R
Last-year Statistics student in Montevideo, Uruguay. Focused on Data Science.
+1 year as Data Analyst.
I am Lucca Frachelle, but everyone calls me Frache. Currently, I am in my final year of a degree in Statistics. My interest leans towards data science, exploring how data can tell stories and reveal hidden truths in numbers and trends.
In my professional role as a Data Analyst, I focus on transforming raw data into actionable insights for strategic decision-making. I achieve this by developing interactive dashboards with Qlik, conducting in-depth data analysis using Python, and building Machine Learning models for churn prediction.
Among my projects, I've explored UMAP and t-SNE algorithms for data visualization and built Machine Learning models to predict successful football plays using FIFA World Cup data from 2022 and 2023.
When I'm not immersed in studying or data, you can likely find me on chess.com, playing chess at an average level. I also hold a barista certification, a testament to my love for coffee and my ongoing interest in learning new skills. Fundamentally, my curiosity drives me to explore how data can enrich our lives, approaching everything with a relaxed yet deeply passionate attitude.