DocsIntroduction

Introduction to EIG Eval

A comprehensive platform for football player evaluation using predictive analytics and machine learning.

What is EIG Eval?

EIG Eval (Elite Insight Grade Evaluation) is a data science platform designed for football analytics. It provides predictive models that evaluate college football players and project their likelihood of success at the professional level.

The platform is built for NFL front offices, college football programs, and analytics departments who need transparent, validated, and actionable player evaluation tools.

Core Concepts

EIG Score

The Elite Insight Grade is a composite score (0-100+) that represents a player's projected NFL success probability. Scores are calculated using position-specific models that weight college production, athletic profiles, and draft capital.

Tier Classifications

Players are classified into tiers based on their EIG score:

  • Elite+88.00 - 100.00+ (highest probability of NFL success)
  • Elite80.00 - 87.99
  • Elite Lite70.00 - 79.99
  • Upside65.00 - 69.99
  • OutlierBelow 65.00

Position-Specific Models

Each position has a dedicated model with tailored feature weights. A wide receiver is evaluated differently than a running back. This ensures the most accurate projections for each position group.

Key Features

Model Registry

All models are documented, versioned, and auditable. View feature weights, training data, and historical performance for complete transparency.

Historical Database

Access 6+ years of graded prospects with NFL outcome tracking. See how past predictions performed against actual professional results.

Validation Framework

Every model is backtested against historical draft classes. Accuracy metrics, hit rates, and calibration data are published for each model.

Real-Time Grades

Current draft class prospects are graded and updated as new data becomes available. Sortable, filterable, and exportable.

Who Should Use EIG Eval?

  • NFL Analytics Departments — Integrate EIG scores into draft boards and player evaluation workflows.
  • College Program Analytics — Evaluate recruiting targets and project player development trajectories.
  • Scouting Departments — Supplement traditional film study with quantitative analysis and data-driven insights.
  • Front Office Personnel — Make informed draft and roster decisions backed by validated predictive models.