
Sun Belt Conference
Women's Basketball · 14 teams · 183 scored athletes
Last updated: October 22, 2026 · refreshed daily
Avg NIL Score
Teams

James Madison Dukes
11 scored players
56.6
Avg

Troy Trojans
13 scored players
53.8
Avg

Louisiana Tech Lady Techsters
9 scored players
52.5
Avg

Georgia Southern Eagles
14 scored players
52.3
Avg

App State Mountaineers
15 scored players
52.0
Avg

Arkansas State Red Wolves
18 scored players
51.9
Avg

Marshall Thundering Herd
13 scored players
51.4
Avg

South Alabama Jaguars
12 scored players
49.1
Avg

Southern Miss Lady Eagles
16 scored players
48.2
Avg

Coastal Carolina Chanticleers
9 scored players
48.2
Avg

UL Monroe Warhawks
17 scored players
46.5
Avg

Old Dominion Monarchs
15 scored players
44.9
Avg

Louisiana Ragin' Cajuns
9 scored players
44.9
Avg

Georgia State Panthers
12 scored players
43.4
Avg
Top Athletes

Joi Williams
G · App State Mountaineers

Zay Dyer
F · Troy Trojans

Ashanti Barnes
F · James Madison Dukes

Jakayla Johnson
G · Southern Miss Lady Eagles

Ja'Quoia Jones-Brown
G · James Madison Dukes

Fortuna Ngnawo
F · Troy Trojans

Destiny Garrett
G · Georgia Southern Eagles

Nakiyah Mays-Prince
G · UL Monroe Warhawks

Emma Smith
G · App State Mountaineers

Crislyn Rose
G · Arkansas State Red Wolves
Methodology
The NILmetrics Score is a 0-100 rating that combines on-court performance, market demand signals, social presence, and risk assessment into a single number. Like Elo for chess or KenPom for basketball, it measures a player's relative standing in the college basketball NIL market — not a guaranteed dollar value or future deal price.
Performance weighs recent box-score production. Market reflects program tier, conference visibility, and demand signals. Social captures verified follower scale. Risk Assessment rewards durable availability over a full sample (a higher score means lower risk). Scores recalculate daily after the overnight game sync, with a full data refresh every Sunday.
Methodology note: women's basketball calibration is developing as the dataset grows. Treat scores as directional while the sample expands.
Read the full methodology →