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Participants must be current or former data professionals (Data Analysts, Analytics Engineers, Data Engineers, Data Scientists, etc.).
Solo participation only (no teams).
Must have hands-on experience with SQL, dbt™, and Git.
Participants must use, but are not limited to, the following tools:
Paradime for SQL & dbt™ development.
Snowflake for data storage and compute.
Lightdash for data analysis and visualizations.
GitHub repository for version control.
Must be able to explain their code and insights. You can use ChatGPT, but you better understand it! 🤣
Value of insights (1-10):
Are the insights interesting and relevant?
Complexity of insights (1-10):
Are you creating meaningful relationships between datasets and providing in-depth analysis?
Quality of materials (1-10):
Is your work polished and professional?
Integration of new data (1-10):
How effectively have you leveraged additional datasets to enhance your findings?
For all technical support and challenge inquiries, use Paradime's #fantasy-football-challenge Slack channel.
Yes. While your submission must be your own work, you can use your network, online resources, and even ChatGPT for inspiration and learning.
Yes, incorporating additional data is required. The sample data we provide is optional.
No. We provide you the following resources:
Paradime for SQL & dbt™ development.
Lightdash for Data Visualizations and Insights
Snowflake Data Cloud for compute and storage.
A pre-configured GitHub repository with example data models to jumpstart your project
Yes, incorporating additional data is required. The sample data we provide is optional. Any data you bring in must be user-generated social media data or relevant supplementary data.
Not exactly. This is a 4-week, asynchronous competition. Participants work on their own time and submit by the deadline (February 4, 2025)
Winners will receive an Amazon e-gift card via email.
Aim to generate accurate and interesting insights. They should be "scroll stoppers"! Some ideas to explore:
Potential Insight Areas with Pre-Loaded Datasets:
Top Performers by Week/Season: Using player_stats_by_game, identify highest-scoring players each week and over the season.
Team Defense Impact: Using play_by_play, determine which defenses give up the most fantasy points by position.
Red Zone Efficiency: Using play_by_play, pinpoint which players or teams excel in scoring opportunities inside the 20-yard line.
Potential Insight Areas with External Datasets:
Top scoring players by week/season
Player consistency analysis (boom/bust metrics)
Impact of team matchups on player performance
Identifying players with high injury propensity
Forecasting 2025 draft prospects
High-cost/low-value player analysis
Exploring fantasy football drafting strategies:
Best Player Available (BPA)
RB-Heavy early drafting
Balanced roster construction
And more...
