Maithili Puntambekar

IPL Match Analytics Dashboard

Cricket discussions are often driven by opinions around toss advantage, player performance, and scoring momentum. However, there is limited data-backed analysis explaining which factors genuinely contribute to winning IPL matches. This project aims to analyze IPL ball-by-ball datasets across multiple seasons to identify: Whether winning the toss significantly impacts match results Which match phase contributes most toward victory Which batters and bowlers consistently perform at the highest level The goal was to transform raw cricket data into meaningful insights using analytics, visualizat Process The project followed a structured analytics approach starting from raw dataset collection to insight generation and visualization. The process included: Collecting IPL ball-by-ball datasets Cleaning and preprocessing data Categorizing overs into match phases Comparing winning and losing team patterns Evaluating player performances Building charts and visual dashboards Drawing insight-driven conclusions Results Toss Advantage Was Limited- The analysis showed that winning the toss had only a moderate influence on match results, proving that overall gameplay performance mattered more. Death Overs Had Highest Impact- Teams that scored efficiently during death overs consistently showed stronger winning patterns compared to teams relying only on powerplay scoring. Consistency Outperformed - Top-performing players maintained consistent contributions across seasons rather than depending only on occasional high-impact performances. Data Revealed Hidden Match Patterns- uncovered trends not visible in matches Reflection Focused on Insight-Based Storytelling Instead of Just Charts - Instead of only visualizing numbers, the project focused on explaining: Why certain patterns occurred, how match phases influenced outcomes, and what separated the winning and losing teams. Used Phase-Wise Match Analysis - Rather than analyzing total scores alone, the project divided matches into: Powerplay, Middle Overs, and Death Overs. Maintained Analytical Accuracy - The analysis excluded dismissals like run-outs while evaluating bowlers to ensure accurate performance measurement. Converted Raw Sports Data into Business-Style