Fantasy Football Analytics

Personal Project | PostgreSQL, SQL, pgAdmin, Data Analytics

Analyze and rank NFL offensive players based on fantasy performance. This project demonstrates end-to-end database design, data ingestion, scoring logic, and analytics queries.

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Project Overview

This project simulates a fantasy football analytics engine:

• Stores player information, weekly stats, and calculated fantasy points.
• Calculates PPR (point-per-reception) and standard fantasy points.
• Generates weekly rankings, positional leaderboards, average points, and consistency metrics.
• Designed to showcase SQL skills including table design, constraints, indexes, joins, aggregates, and window functions.

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Database Schema

Tables

Table	Description
players	Stores player info (name, position, team). Primary key: player_id.
weekly_stats	Stores weekly performance stats (passing, rushing, receiving, turnovers). Linked to players via player_id.
fantasy_points	Stores calculated PPR and standard fantasy points per player per week. Linked to weekly_stats via player_id and week.

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Entity Relationship Diagram

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Technologies & Skills Demonstrated

• Database Design: Relational schema with primary and foreign keys, indexes, and constraints.
• SQL: Aggregations (AVG , STDDEV), window functions (RANK , PARTITION BY, LAG), JOINs, INSERT statements, and SELECT statements.
• Analytics: Fantasy points calculation, weekly rankings, positional leaderboards, and player consistency.
• Tools: PostgreSQL, pgAdmin
• Project Workflow: Data ingestion -> Scoring -> Analytics -> Insights

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Next Steps

• Add more players and weeks to simulate an entire NFL season.
• Build visualizations in Python using database outputs.
• Add dynamic queries to compare PPR vs standard scoring.

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Usage

1. Clone the repository.
2. Run schema.sql to create tables.
3. Run seed_data.sql to populate sample data.
4. Run fantasy_scoring.sql to calculate fantasy points.
5. Run analytics_queries.sql to generate rankings and insights.

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Contact

Created by Michael John.
Feel free to connect with me on LinkedIn.