This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
online
1,145
Participants
₹5,000
Prize Pool
103
Est. Projects
Ipl Crunch ’26: Opportunity Description: Everyone has IPL opinions. Very few can back them with data. IPL CRUNCH ’26 is an online data analytics challenge by Wooble where participants work with real IPL match datasets to uncover patterns, answer high-impact cricket questions, and present insights through charts, analysis, and storytelling. This is not a quiz. This is proof of skill. Participants will work with real ball-by-ball IPL data and solve practical analytics problems similar to how analysts work in sports, product, and business environments. What You Need To Do: You will analyze IPL data and answer questions such as: Do teams that win the toss actually win more matches? Which phase impacts victory the most — Powerplay, Middle Overs, or Death Overs? Who are the top batters and bowlers across seasons? What hidden patterns or surprises can you discover from the data? Participants are expected to: Clean and process datasets. Perform exploratory data analysis. Build charts/visualizations. Draw conclusions backed by data. Present findings clearly. Dataset: Participants can use IPL datasets from: Cricsheet.org (JSON format) OR. CSV files provided in the challenge resources here. You may use Python, Excel, SQL, Power BI, Tableau, or any analytics tool of your choice. Submission Format: Participants must submit: Analysis Report / Presentation. Charts & Visualizations. Source Code / Notebook / Dashboard Link. One key insight that genuinely surprised you. Accepted formats include: PDF. PPT. GitHub Repository. Google Colab. Dashboard Links. Why Participate?: Work on a real-world analytics challenge. Build proof of work for your portfolio. Showcase analytical thinking publicly. Compete with data enthusiasts across India. Stand out beyond resumes and certificates. Rules: Original work only. Plagiarism will lead to disqualification. Multiple submissions are not allowed. Participants may use AI tools for assistance, but final interpretation and work must be their own. Decision of the organizers will be final.
Judge Accessibility
Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10
Top signals
Organizer email available
Student-run event
Actively looking for judges
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
Sam Chen
sam@example.org
Estimated Audience
Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech
Technical Focus
AI95%
Web80%
Mobile25%
Industries
Healthcare
Education
Climate
Technologies
Python
React
OpenAI
Why this estimate
• Hosted by a university
• Open to students
• MLH member event
Estimate inferred from event metadata, not actual attendee data.