{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/1496af3ce1ff4d3a895fe833f8c176b7\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/1496af3ce1ff4d3a895fe833f8c176b7-a31d180d130dc778.gif","duration":131.519,"title":"IPL Match Data Analysis, Toss and Phases","description":"This Loom presents an IPL match data analysis using Python, Pandas, Matplotlib, and Jupyter Notebook to answer questions from ball-by-ball data. It examines whether teams that win the toss also win more matches by converting Cricut Bluetooth data and JSON files into CSV, then comparing toss winners versus match winners across multiple seasons in a bar chart. The analysis finds the toss advantage is much smaller than many people expect. It also performs phase analysis of average run per phase, comparing powerplay, middle, and death overs, and concludes that strong death-overs performances are more strongly linked to victories. Finally, it identifies the top 5 batsmen and top 5 bowlers with supporting visualizations and a summary table."}