Education Data Source Eada

EADA Data Source Reference

Equity in Athletics Disclosure Act (EADA) data for college athletics gender equity analysis covering ~2,000+ institutions (2002-2021). Use when analyzing athletic participation, coaching staff, salaries, expenses, revenues, or athletic aid by gender at colleges/universities, or understanding Title IX context in athletics. EADA is NOT Title IX compliance data. Note: no sector column; join to IPEDS on unitid to filter by institution type.

The EADA provides the only standardized, publicly available dataset on college athletics participation, coaching, finances, and athletic aid by gender across ~2,000+ postsecondary institutions, enabling gender equity analysis in intercollegiate athletics.

CRITICAL: Value Encoding

EADA data from the Education Data Portal uses integer codes for categorical variables. Original EADA web tools use string labels; the Portal converts these to integers. Always verify codes against the codebook (see Truth Hierarchy below).

Context	ath_classification_code	Missing values
Portal (integers)	1 = NCAA DI FBS	-1, -2, -3
Original EADA	String labels	Blank / N/A

Note: There is no sector column in EADA Portal data. To filter by sector, join with IPEDS directory data on unitid.

See ./references/variable-definitions.md for complete encoding tables.

What is EADA?

• Collector: U.S. Department of Education (Office of Postsecondary Education)
• Coverage: ~2,000+ coeducational postsecondary institutions with intercollegiate athletics
• Mandate: Institutions participating in Title IV aid with athletic programs must report
• Frequency: Annual (data publicly available by October 15 each year)
• Available years: 2002–2021 (Portal mirror)
• Primary identifier: unitid (6-digit IPEDS institution ID)
• Content: Athletic participation, coaching staff, salaries, expenses, revenues, and athletic aid — all reported by gender
• Available through: Education Data Portal mirrors

Reference File Structure

Decision Trees

What analysis am I conducting?

Research question?
├─ Gender equity overview → Start with participation + aid ratios
│   └─ See ./references/data-elements.md
├─ Coaching disparities → Coach counts + salaries by gender
│   └─ See ./references/data-elements.md (Coaching section)
├─ Financial investment → Expenses + revenues by team gender
│   └─ See ./references/data-elements.md (Financial section)
├─ Sport-specific analysis → Individual sport data
│   └─ See ./references/sport-level-data.md
├─ Title IX compliance assessment → CAUTION: EADA ≠ compliance data
│   └─ See ./references/limitations.md (Critical)
└─ Trend analysis → Year-over-year comparisons
    └─ See ./references/fetch-patterns.md

What variables do I need?

Variable categories?
├─ Participation counts
│   ├─ Unduplicated by gender → `undup_athpartic_men`, `undup_athpartic_women`
│   ├─ Duplicated (sport-level sum) → `athpartic_men`, `athpartic_women`
│   ├─ Coed teams → `athpartic_coed_men`, `athpartic_coed_women`
│   └─ By sport → See ./references/sport-level-data.md
├─ Coaching
│   ├─ Head coaches → `men_fthdcoach_*`, `women_fthdcoach_*` variables
│   ├─ Assistant coaches → `men_ftascoach_*`, `women_ftascoach_*` variables
│   └─ Salaries → `hdcoach_salary_*`, `ascoach_salary_*` variables
├─ Financial
│   ├─ Expenses → `ath_exp_*` variables
│   ├─ Revenues → `ath_rev_*` variables
│   └─ Athletic aid → `ath_stuaid_*` variables
└─ Detailed definitions → See ./references/variable-definitions.md

How do I interpret the data?

Interpretation question?
├─ What counts as "participation"?
│   └─ See ./references/variable-definitions.md
├─ Why don't participation ratios match enrollment?
│   └─ See ./references/limitations.md
├─ Is this institution Title IX compliant?
│   └─ CANNOT determine from EADA data alone
│       └─ See ./references/limitations.md (Critical)
├─ Why are some values missing or zero?
│   └─ See ./references/limitations.md
└─ How do I compare across institutions?
    └─ See ./references/limitations.md (Comparability section)

Quick Reference: Key Metrics

Participation Equity Indicators

Financial Equity Indicators

Coaching Equity Indicators

Key Identifiers

Common Filters

Note: There is no sector column in the EADA Portal data. To filter by institutional sector, join with IPEDS directory data on unitid.

Athletic Classification Codes

Note: Code 1 was historically labeled "NCAA Division I-A" and code 2 "NCAA Division I-AA" in earlier years. The ath_classification_name string column reflects the label used at the time of reporting.

Missing Data Codes

Data Availability

Note: Some columns (e.g., num_sports, aggregated totals with _all suffix) are null for earlier years (2002) and were added in later reporting cycles. The opeid column is null for 2002.

Example Research Questions

Data Access

Datasets for EADA are available via the Education Data Portal mirror system. All data fetching uses fetch_from_mirrors() from fetch-patterns.md, with mirrors defined in mirrors.yaml and canonical paths in datasets-reference.md.

Key datasets:

EADA naming note: The data path uses inst_characteristics (underscores) while the codebook path uses inst-characteristics (hyphens). Always use the exact paths from datasets-reference.md.

Truth Hierarchy

When interpreting EADA variable definitions and coded values, apply this priority:

Use get_codebook_url("eada/codebook_colleges_eada_inst-characteristics") from fetch-patterns.md to construct the codebook download URL.

Filtering

import polars as pl

# Filter by athletic division (NCAA Division I FBS only)
df_d1_fbs = df.filter(pl.col("ath_classification_code") == 1)

# Exclude coded missing values before calculations
df_clean = df.filter(
    (pl.col("undup_athpartic_men") >= 0) &
    (pl.col("undup_athpartic_women") >= 0)
)

# Note: No `sector` column in EADA data. To filter by sector,
# join with IPEDS directory data on unitid first.

Common Pitfalls

EADA vs. Title IX Compliance

EADA Data                          Title IX Compliance
──────────────────────────────────────────────────────────
Self-reported                      OCR investigation
Snapshot (Oct 15)                  Continuous obligation
Participation counts only          Participation + interest + ability
No "laundry list" items           13+ treatment areas
Public disclosure                  Enforcement mechanism

Always read: ./references/limitations.md before drawing compliance conclusions.

Key Limitations Summary

• Self-reported: No independent verification
• Counting methods: Differ from Title IX counting
• Not comprehensive: Misses many equity factors
• Comparability issues: Different reporting practices across institutions

Related Data Sources

Topic Index