Samridhi nirayanwal

IPL Data Analysis Project -Turing raw data into insights

IPL has tons of match data but no clear way to see what actually wins games — teams and analysts make decisions based on gut feeling, not data. Process Started by identifying the key questions that matter in cricket — not just "who scored most runs" but deeper stuff like phase-wise contribution, toss impact and win patterns. Then collected IPL dataset covering all seasons, cleaned and structured it properly, and designed a dashboard that answers these questions visually without making the viewer do mental gymnastics. Results Toss is overrated — With a 50.2% vs 49.8% win rate, toss has almost zero impact on match result. Pure myth busted with 1218 matches worth of data Middle overs are the real game — 44% of all runs are scored in middle overs, more than powerplay and death overs. This changes how you think about batting strategy Bat first wins more — Teams defending win 53.9% of the time vs 46.1% while chasing. Across 1218 matches that's a statistically significant pattern Kohli is in a different league — 9399 runs in 268 matches vs Rohit's 7548 in 271 matches. Nearly same games, 1800 runs difference — that's con Reflection Venue intelligence — Some grounds are batting paradises, some are bowler friendly. Would add a venue-wise breakdown so teams can see location-specific patterns before going in Player form vs career stats — Right now the dashboard shows career totals which can be misleading. A player could have had 3 bad seasons recently. Would add last 3 season form to make it more relevant Batter Strike Rate analysis — Total runs alone can be misleading. A batter scoring 500 runs at SR 110 is very different from one scoring 500 at SR 145. Would add strike rate alongside runs to show how fast players score