Tanya Garg
Featured project
IPL Match Analytics — What Actually Wins IPL Games?
IPL discussions are often based on assumptions like “winning the toss guarantees victory” or “powerplay overs decide matches.” This project aimed to test those assumptions using real IPL ball-by-ball data from 5 seasons. The goal was to identify which factors truly impact match outcomes by analyzing toss results, phase-wise performances, and player statistics through data visualization and exploratory analysis. Process I collected IPL datasets in CSV format and analyzed them using Python and Pandas. The first step involved cleaning missing values, organizing match records, and dividing innings into Powerplay, Middle Overs, and Death Overs. I then performed exploratory data analysis to compare winning and losing teams based on runs, wickets, and toss outcomes. Multiple visualizations were created using Matplotlib to identify patterns and trends. Different chart layouts and comparison methods were tested before selecting the most readable and insight-driven visuals. The final report summarized findings with charts, tables, and concise explanations. Results The project analyzed over 240,000 ball-by-ball IPL records and converted raw data into meaningful insights. The analysis showed that toss advantage had a smaller impact on match results than commonly believed, while strong death-over performances were closely linked to victories. Top-performing batters and bowlers across seasons were identified using statistical analysis. The project improved my skills in data cleaning, visualization, exploratory analysis, and storytelling with data. Reflection If I continue this project, I would build an interactive dashboard using Power BI or Tableau to make the analysis more dynamic. I would also include venue-based performance analysis, player pressure metrics, and predictive models to forecast match outcomes. Integrating live IPL APIs and advanced machine learning techniques could further improve the depth and real-time capabilities of the project.