jocheanima-cpu/Ghana-Black-Queens-Attacking-Performance-Analysis-WAFCON-2026-

Ghana Black Queens: Attacking Performance Analysis - WAFCON 2026 Submitted in fulfillment of the requirements for the Sports Analytics track of the Because She Can Mentorship Programme. Overview: This is a data analytics project I put together to look at how Ghana's Black Queens performed in attack across their WAFCON 2026 campaign, which ended with a 2–1 quarter-final loss to Malawi after a group stage of one win, one draw, and one loss. I used their match data to try and understand what actually happened to the campaign and why it ended the way it did. Objective: To clean and analyse Ghana's match-level attacking data and figure out what the numbers actually say about why the team won, drew, or lost each game - and specifically what changed (or didn't) between the matches. Dataset: Source: SofaScore (I compiled the match stats manually) Scope: All 4 of Ghana's WAFCON 2026 matches - vs. Cabo Verde, Cameroon, Mali, and Malawi Format: CSV, about 20 variables per match (shots, shots on target, possession, fouls, cards, corners, free kicks, etc.) Note: Possession percentage wasn't available for the Cabo Verde match, so I left it blank instead of guessing a number. Methodology: I cleaned and analysed the data using Pandas, and built the visualisations in Matplotlib. I also created two columns of my own to separate chance creation from finishing: Metric Formula What it measures: Shot Accuracy Shots on Target ÷ Total Shots How often Ghana's attempts actually threatened the goal. Goal Conversion Goals ÷ Shots on Target Of the real chances created, how many were actually finished Key Findings: Ghana's shot volume was highest against Cabo Verde (21 shots), but their most accurate match (70% shot accuracy) was actually the Malawi quarter-final which was the match that ended their run. Shot Accuracy and Goal Conversion moved in more or less opposite directions across the tournament, which shows that creating chances didn't reliably translate into finishing them. Poor …