Built a data-driven model to objectively identify top players of the 2021–2022 UCL season using advanced analytics.
Analyzed UEFA Champions League 2021–2022 season data to objectively identify top-performing players by position, moving beyond reputation-based selections. The project tackled messy datasets that lacked unique player identifiers, leading to duplicates and inconsistencies across sources.
To address this, unique identifiers were created and used to merge multiple datasets using SQL, ensuring data integrity. A custom, position-weighted points system was then designed for goalkeepers, defenders, midfielders, and forwards, incorporating advanced metrics like clean sheets, tackles, tackle %, goal contributions, ball recoveries, distance covered, red cards, and more.
Data cleaning and transformation were handled in Python using Pandas and NumPy, while Tableau was used to build interactive dashboards visualizing rankings and player performance trends.
Key insights:
The model showed that six of the eleven players in the data-driven team matched the official UEFA Team of the Season—validating the approach. More importantly, it surfaced undervalued defenders and midfielders, highlighting how a comprehensive scoring model can reveal true player impact often missed by traditional stats.
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