What's included

• Web Scraping Scripts

  Custom-built Python scrapers (Selenium, BeautifulSoup, or API integrations) to automatically collect structured data from dynamic sports websites.

• Clean & Structured Datasets

  Processed CSV/Excel files containing player stats, match results, odds, or historical records — ready for direct analysis or integration.

• Data Processing & Cleaning

  ETL workflows to handle missing values, remove duplicates, and standardize metrics for accurate analysis.

• Exploratory Data Analysis (EDA)

  Summary statistics, trends, and visualizations to uncover key insights from raw sports data.

• Predictive Modelling

  Machine learning models for outcome prediction (e.g., match results, player performance) with documented accuracy metrics.

• Custom Dashboards / Reports

  Interactive dashboards (Tableau/Matplotlib/Seaborn) or static PDF reports to visualize insights and support decision-making.

• Documentation & Reproducibility

  tep-by-step usage instructions and code documentation so you (or your team) can easily maintain and extend the project.