FPL On Target is a data-driven analytics project designed to help Fantasy Premier League (FPL) users make informed player selections based on key shooting and performance metrics. The project leverages Python for data scraping and Power BI for visualization, offering a detailed interactive report that showcases player efficiency in front of goal.
✔ Web Scraping with Python – Extracts detailed player and team statistics from FBref.
✔ Data Processing – Cleans and structures data into CSV datasets for easy analysis.
✔ Power BI Dashboard – Visualizes key performance metrics including goals, assists, xG, shots on target, and possession stats.
✔ Fantasy Premier League (FPL) Insights – Helps FPL users identify high-performing players for their teams.
The Power BI report analyzes FPL player performance with key metrics, including:
✔ Top-performing players – Ranked by goals, assists, xG (expected goals), shots on target, and minutes played.
✔ Player Performance Overview – A line chart comparing xG, goals scored, and shots on target.
✔ Player Performance Metrics – A scatter plot highlighting outliers and trends in player statistics.
✔ Interactive Filters – Users can filter players by position, team, or individual selection for dynamic exploration.
📌 Python Script (pl_data_scraper.py) – Scrapes data from FBref and processes it into structured datasets.
📌 Datasets (pl_player_stats.csv, pl_team_stats.csv) – Contains detailed player and team performance data.
📌 Power BI Dashboard (pl_on_target_analysis.pbix) – Provides interactive visual analytics to aid FPL decision-making.
1️⃣ The Python script scrapes Premier League data from FBref.
2️⃣ The data is cleaned and processed into structured CSV files.
3️⃣ The Power BI report visualizes player performance trends, allowing users to explore insights dynamically.
🔹 Python (BeautifulSoup, Pandas, Requests)
🔹 Power BI (Data visualization)
🔹 CSV Processing (Data storage and analysis)