IPL DATA ANALYSIS (2023-2026)

There is massive amount of raw ball-by-ball IPL data available every season, but it is difficult to interpret, compare, and derive meaningful insights from. The objective of this project is to transform raw IPL ball-by-ball data (2023–2026) into an interactive analytics dashboard that enables users to explore, analyze, and visualize cricket performance through advanced statistical metrics and dynamic insights. Process The project started with collecting raw IPL ball-by-ball datasets (2023–2026). The first step involved understanding the dataset structure, cleaning inconsistencies, and organizing the data into a usable format. Before development, I created a rough analytical framework to identify important cricket statistics and the type of insights useful for fans, analysts, and team management. Based on cricket knowledge and game context, several custom scoring formulas and analytical metrics were developed. Finally, I improved the UI and layout to make the dashboard visually professional, interactive, and user-friendly through filters, charts, structured layouts, and responsive navigation. Results The dashboard provides information about top performing batsman and bowlers and then dive deep into venue analysis, each player analysis as well as analysis of all 10 teams. Several custom scoring formulas and analytical metrics are developed by me. These included: phase-wise role classification, matchup analysis, venue-based trends, and advanced batting/bowling insights. The dashboards provide various filters to help users in analysis and almost every analysis in associated with graphs to help user visualize the data. Reflection I believe rather than just numbers , I combined those numbers and instead of relying on just quantitative analysis , also calculated qualitative analysis of players, teams and venues. Because in cricket matches, numbers alone can be misleading. Therefore it is important to analyze quality of metrics rather than just quantity. Also instead of basic cricket dashboards which are restricted to runs, wickets, win% , loss % , I really tried to dive and touch all major metrics related to cricket analysis (like phase-wise scores , toss results , venue impact, and team performance)