IPL Crunch '26: What Actually Wins Matches — A Ball-by-Ball Intelligence Report

IPL discussions are driven by opinion, not evidence. Pundits claim the toss decides matches, coaches obsess over powerplay starts, and fans debate death-over specialists — but nobody had quantified which factor actually separates winners from losers across all 17 IPL seasons. The gap: 260,759 ball-by-ball deliveries existed but no structured analysis had tested these claims statistically. Process Built a two-module Python pipeline: data_engine.py for all feature engineering (phase assignment, dot ball flags, winner labels) and chart_engine.py for 14 production-grade Plotly visualisations. Applied binomial significance testing on the toss claim, computed RPO gaps per phase across all seasons, and built composite weighted scoring systems for batters and bowlers — validated against known elite performers. Results Toss win rate = exactly 50.0% across 1,095 matches (p=1.000 — not significant). Death-over RPO gap = +2.04 (worth +12.2 runs per match), positive in all 17 of 17 seasons — 100% consistency rate. V Kohli ranked #1 batter composite. YS Chahal ranked #1 bowler. Project produced 14 charts, a 5-page PDF report, and an executive dashboard — all from a reproducible two-module pipeline. Reflection With more time I would build a ball-by-ball win probability model using gradient boosting to quantify exactly when momentum shifts during a chase. I'd also add venue-specific phase analysis — the death-over advantage likely varies significantly between small grounds like Wankhede and larger ones like Eden Gardens.