animesh Jain
Featured project
IPL Data Analysis
IPL Crunch ’26 is a data analytics challenge focused on analyzing real IPL ball-by-ball datasets to uncover meaningful cricket insights through visualization and storytelling. The project aims to identify player performances, match-winning patterns, and phase-wise impact using data-driven analysis and interactive dashboards. Process The project began with collecting and cleaning raw IPL ball-by-ball match data using Python and Pandas in Jupyter Notebook. After preprocessing the dataset, advanced cricket metrics such as batting strike rate, bowling economy, dot ball percentage, and phase-wise performance indicators were calculated using DAX in Power BI. The cleaned data was then transformed into an interactive multi-page dashboard focused on overview analytics, batting intelligence, and bowling intelligence. Finally, the project emphasized storytelling-driven insights to uncover tournament trends, player dominance, venue behavior, and match-winning patterns across IPL seasons. Results The project successfully transformed raw IPL ball-by-ball data into an interactive analytics ecosystem capable of delivering batting, bowling, venue, and match-level intelligence. Multiple advanced performance indicators such as strike rate, economy, bowling average, phase-wise scoring, and dot-ball pressure analysis were generated to uncover deeper tournament insights. The dashboard enabled dynamic filtering across seasons, teams, venues, and players, making the analysis highly interactive and user-driven. Overall, the project demonstrated how data analytics can convert cricket statistics int Reflection This project focused on storytelling-driven cricket analytics instead of only displaying basic statistics. Advanced metrics such as phase-wise impact, bowling efficiency, and dot-ball pressure analysis were used to uncover deeper IPL trends. The dashboard was designed with interactive filtering, multi-page analysis, and insight-based visual explanations to create a more strategic and user-focused analytical experience.