Title IX Compliance Dashboards

A dynamic, data-driven command center for managing post-House v. NCAA Title IX compliance, created for the fictional "Cumberland State University".

This project features ten role-based dashboards covering the full compliance stack—from proportionality and financial assistance to athlete wellness and predictive modeling.

Features

Compliance Metrics

1. Participation Proportionality (Prong 1): Real-time delta between female undergraduate share and female athlete share.
2. Scholarship-to-Participation Delta: Athletic Financial Assistance (AFA) ratio with dollars-per-opportunity variance.
3. Laundry List Equity Index: Heat map across treatment-and-benefits sub-parts.
4. Revenue Sharing Equity (RSE): Tracks the $20.5M House-Settlement cap.
5. NIL Fair Market Value Variance: Inflation ratio of collective deals vs. estimated FMV.
6. Mental Health Access Parity: Wait-time delta and counselor-hours per athlete.

Predictive What-If Tools

7. Roster Management: Simulate adding teams, capping walk-ons, or expanding rosters.
8. Predictive Financial Aid Modeling: Model Cost-of-Attendance stipends and balanced-aid offsets.
9. Revenue-Share Simulator: Allocate the settlement cap across teams.
10. NIL GO Clearinghouse: FMV grid of collective deals with safe-harbor classifications.

Data-Driven Architecture

• Dynamic Datasets: All visualizations, metrics, and tables are generated dynamically from underlying CSV datasets. Updating the CSV files in the dataset/ folder immediately reflects in the dashboard without any code changes.
• Built-in Dataset Viewer: Explore, search, and download the raw datasets directly from the dashboard sidebar using a responsive grid interface.

Getting Started

To view the dashboards locally, you must run a local web server (to prevent CORS issues when the JavaScript fetches the local CSV datasets).

You can easily do this using Python's built-in HTTP server:

# Start a local web server in the project directory
python3 -m http.server 8000

Then, open your web browser and navigate to: http://localhost:8000/

Technologies Used

• Vanilla Web Stack: HTML5, CSS3, JavaScript (ES6+)
• Chart.js: For rendering compliance metric charts and what-if visualizations.
• Grid.js: For rendering the responsive, searchable dataset tables.