IPL Match Insights Dashboard

IPL debates are usually based on opinions, team loyalty, or assumptions. This project solves that by using ball-by-ball IPL data to answer 3 questions with numbers: do toss winners win more matches, which match phase is most linked to winning, and who are the top 5 batters and bowlers across 5 seasons. Process I cleaned and analyzed IPL ball-by-ball data using Python and Pandas. I selected the important columns such as toss winner, match winner, batting team, batter, bowler, runs, wickets, and overs. Then I grouped overs into three phases: powerplay, middle overs, and death overs. After that, I calculated toss winner vs toss loser win rate, compared average phase-wise runs for winning and losing teams, and ranked top batters and bowlers across 5 seasons. Finally, I converted the analysis into a Streamlit dashboard with clear charts and tables. Results The final dashboard answers all 3 required hackathon questions. It shows the toss winner vs toss loser win-rate chart, compares average runs across powerplay, middle overs, and death overs, and displays the top 5 batters and top 5 bowlers across 5 seasons. The project turns IPL opinions into simple, data-backed insights. Reflection With more time, I would add filters for team, venue, season, and player. I would also include advanced metrics like strike rate by phase, economy rate, dot ball percentage, boundary percentage, and venue-based chasing advantage. I would also improve the dashboard with more interactive charts and automatic insight summaries.