ashpe-osk/afcon2023-final-analysis

A breakdown of the 2023 Africa Cup of Nations Final between Ivory Coast 🇨🇮 and Nigeria 🇳🇬. Built with StatsBomb open data, mplsoccer, and matplotlib. Covers individual pass maps and team passing network to uncover the tactical patterns behind Ivory Coast's victory. # AFCON 2023 Final - Passing Analysis Python project analyzing how Côte d'Ivoire moved the ball in the AFCON 2023 Final, using StatsBomb's open event data. **Match:** Nigeria vs Côte d'Ivoire, AFCON 2023 Final (11 February 2024) The project looks at the game from two angles: how one player (Jean Michaël Seri) distributed the ball, and how the team as a whole built up play through its passing network. ## What's Included **Player Pass Map**: every pass Seri attempted, plotted on a pitch and split into completed and incomplete, to see his volume, accuracy and the areas he influenced most. **Team Passing Network**: passes between Côte d'Ivoire's starting XI turned into a network, where: * Node size shows how involved a player was in passing * Edge thickness shows how often two players connected ## Output **Player Pass Map** (Jean Michaël Seri, Côte d'Ivoire) **Team Passing Network** (Côte d'Ivoire) ## Key Findings * Seri completed 61 of 66 passes (about 92%), operating as a deep lying playmaker linking defence to attack * The team's build up leaned heavily on the left side and centre, through Konan, Ndicka, Kossonou and Seri * The strongest single passing connection was Konan to Adingra * The right flank (Aurier, Gradel) was comparatively underused ## Project Structure ``` afcon-2023-final-passing-analysis/ │ ├── pass_map.ipynb # Player pass map (Jean Michaël Seri) ├── passing_network.ipynb # Team passing network (Côte d'Ivoire) ├── requirements.txt ├── README.md │ ├── images/ │ ├── pass_map.png │ └── passing_network.png │ └── report/ └── Passing_Analysis_Report.pdf # Full written report ``` ## Tech Stack Python, pandas, numpy, mplsoccer, statsbombpy, matplotlib ## Data Source StatsBomb Open Data, free event level football data for research and education. ## Report Full methodology and interpretation: Passing Analysis Report ## Author Oseko Ashpe LinkedIn: linkedin.com GitHub: htt …