Live Dashboard: cricket_t20
Project Steps:
- 🌐 Requirement Scoping
- 📊 Data Collection via Web Scraping from ESPN Cricinfo
- 🔄 Data Gathering & Transformation: Used BrightData for efficient web scraping, collected player info, and utilized Power Query for analysis. Ensured accuracy through Python (Pandas) for cleaning, preprocessing, and transforming data.
- 📊🛠️ Data Modeling and Collection through Python-based web scraping from ESPNcricinfo.com
- 🔄 Data Transformation and Visualization using PowerBI and DAX queries
- 📊 Dashboard Creation: Developed user-friendly Power BI dashboards, highlighting insights on Power Hitters, Anchors, Finishers, All-rounders, and Top Bowlers.
Key Learnings:
- 🌐 Web Scraping: Explored player profile scraping from ESPNcricinfo.com.
- 🧹 Data Cleanup Choreography: Ensured data cleanliness, removed duplicates, and polished player profiles.
- 📊 Dashboard Discovery: Explored PowerBI, creating visually appealing dashboards, including a Power Hitters Metrics Page and a Player Profile Tooltip.
- 🎯 Player Analysis: Identified top Power Hitters, Anchors/Middle Order players, Finishers, All-rounders, and Bowlers through comprehensive analysis.
- 🏏 Playing 11 Strategy: Formulated a balanced Playing 11, considering players' performance for setting competitive totals and defending.