Project detail
Cricket Analysis Using Power BI and Web Scraping
Objective: The project aimed to extract, analyze, and visualize cricket performance data to provide predictive insights into player and team performance.Key Steps Involved:
Web Scraping: Used Python and BrightData to collect cricket performance data from various sources (e.g., match statistics, player profiles, and historical records). Ensured data integrity by handling missing values and cleaning the dataset using libraries like Pandas and NumPy.Processing:
Organized the scraped data into a structured format for analysis. Derived key performance metrics, such as batting averages, bowling economies, and win rates.Visualization:
Created interactive dashboards using Power BI to showcase trends and insights. Visualized data to highlight top-performing players, team strengths, and match outcomes. Enabled filtering by player, team, and match type for dynamic reporting.Outcome:
Delivered actionable insights for cricket enthusiasts, analysts, and coaches. Facilitated data-driven decision-making, such as predicting player performance or team strategies.