WELCOME TO THE AQX SPORTS ANALYTICS DATA BOWL 4.0!

AQX Sports Analytics Data Bowls are 100% free, fully virtual, open-source competition designed for those interested in sports analytics, programming, and data science.

Whether you want to predict the next NBA MVP, build an algorithm to optimize fantasy football success, or analyze MLB swing mechanics using statcast, this is the opportunity to do so. 

Ready to change the game? What are you waiting for? Let's get to it!

Requirements

WHAT TO BUILD

The Core Project: Build a software application, web application, interactive dashboard, or predictive model centered around sports analytics, with the flexibility to choose any sport you wish.

Data: Your project must utilize some form of sports data (e.g., player tracking, team statistics, sports business metrics, or injury data) to formulate analytical insights to solve a sports-based problem

This hackathon is an open-source competition!

WHAT TO SUBMIT

Submit a working prototype along with your public source code (GitHub) and a short project description detailing your solution, features, and actionable impact, no video demo required, although you may submit one if you like.

Projects unrelated to sports analytics will not be judged or acknowledged.

Projects from previous AQX Sports Analytics Data Bowls will not be accepted, and will result in immediate disqualification.

Hackathon Sponsors

Prizes

4 non-cash prizes
First Place Honors
1 winner

First Place Honors!

Second Place Honors
1 winner

Second Place Recognition!

Third Place Honors
1 winner

Third Place Recognition!

Honorable Mentions
1 winner

We will recognize two honorable mentions!

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

AQX Analytics

AQX Analytics
AQX Analytics

Judging Criteria

  • Practical Application
    Could a coach, front office, or athlete benefit from your findings? The project should solve a real gap in sports analytics, such as improving player performance, injury risk reduction, or enhanced game strategy to name a few.
  • Analytical Insight
    How well did your project dive into the data. How statistically sound were your methods? How accurate was your data modeling? Discovering actionable insights is highly favorable over surface level statistics.
  • Data Presentation
    How well was the data communicated? How clear was the data delivered (visualizations, dashboards, charts, etc), as well as the individual(s) ability to pitch their discoveries clearly and concisely to an audience that would not be as technically sound.

Questions? Email the hackathon manager

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