Tag IPL highlights for analytics

Cricket video analysis is usually treated like a pro setup problem — expensive feeds, proprietary data, specialist tooling. But for a beginner, that can be the wrong place to start. The useful news here is simpler: the official IPL 2025 MI vs RCB highlights are still live, and Mumbai Indians’ own “MI Daily” upload from May 10, 2026 is live too. That gives you two different kinds of footage to tag right now — one match package, one team-context package. ### Why these two videos matter? The IPL highlights clip is the clean event layer. It compresses the match into a 14:01 package and sits on the official IPL site, which makes it a practical source for manual logging of wickets, boundaries, batting phases, bowling changes, and chase pressure moments. The MI Daily video is different — less about every ball, more about mood, prep, travel, and framing. Put together, they let you separate on-field events from off-field context. (iplt20.com) ### What exactly was the match? The official IPL page identifies this as IPL 2025 Match 21, Mumbai Indians vs Royal Challengers Bengaluru, played on April 7, 2025. The searchable page text also carries the core result: RCB made 221/5, MI replied with 209/9, and Bengaluru won by 12 runs, with Rajat Patidar named player of the match. That is enough structure to anchor a tagging exercise around innings phases and turning points. (iplt20.com) ### What should a beginner tag first? Start with a dumb spreadsheet, not a fancy dashboard. Log innings, over, batting team, striker, bowler, event type, and outcome. Event type can stay simple: dot, single, two, three, four, six, wicket, extra. Then add a second layer — dismissal type, boundary side, over phase from 1-6, 7-15, 16-20, and a short note for momentum swings. Basically, you are creating the smallest dataset that still lets you ask real questions. (iplt20.com) ### Why add the MI Daily video? Because highlights alone flatten the story. A chase can look like pure batting variance when it was really shaped by pitch talk, lineup mood, or role clarity. Team-produced daily videos will not give you neutral truth — that is the catch — but they do give you timestamps for preparation, player focus, venue conditions, and what the franchise itself thought mattered that day. “MI Daily 2026: May 10 - Sunday blockbuster in Raipur” is exactly that kind of context artifact. ### What can you do with the dataset? A lot, actually. You can chart boundary frequency by phase, compare wicket clusters against required run rate, or mark whether momentum changed after a timeout, a dropped chance, or a bowling switch. In Excel, that becomes pivot tables and a worm chart. In Tableau, it becomes a cleaner match-flow visual. The point is not to mimic CricViz on day one — it is to prove you can turn raw video into structured evidence. (youtube.com) ### What is the hard part? Consistency. Manual tagging falls apart when your labels drift. If one six is “aggressive intent,” another is “boundary,” and a third is “release shot,” your dataset is already noisy. Write a tiny codebook first. One line per field. One definition per label. Think of it like scoring baseball — boring upfront, but it saves the whole project later. ### What would a good output look like? One page. That is enough. Open with the match result, explain your tagging method, show two visuals, and make three claims you can defend from the data. For example: RCB’s scoring pressure stayed high through middle overs, MI’s wickets came in clusters, and the chase hinged on a short sequence rather than one final-over collapse. ### Bottom line? If you want a realistic entry-level cricket analytics exercise, this is a good one. The official MI-RCB highlights give you the event spine, and the MI Daily upload gives you surrounding texture. That is enough to practice the real job — watching closely, labeling cleanly, and turning a match into something analysts can actually use.