Atlantic Coast Conference
Power 4Women's Basketball · 18 teams · 190 scored athletes
Last updated: September 5, 2026 · refreshed daily
Avg NIL Score
Teams
NC State Wolfpack
10 scored players
62.7
Avg
Louisville Cardinals
14 scored players
60.7
Avg
Virginia Tech Hokies
10 scored players
60.1
Avg
Duke Blue Devils
8 scored players
60.0
Avg
Wake Forest Demon Deacons
11 scored players
59.5
Avg
Notre Dame Fighting Irish
5 scored players
59.3
Avg
North Carolina Tar Heels
13 scored players
59.2
Avg
Stanford Cardinal
15 scored players
58.5
Avg
Georgia Tech Yellow Jackets
9 scored players
58.3
Avg
Florida State Seminoles
9 scored players
56.9
Avg
Miami Hurricanes
11 scored players
56.1
Avg
Virginia Cavaliers
10 scored players
55.1
Avg
California Golden Bears
11 scored players
54.4
Avg
Clemson Tigers
10 scored players
53.7
Avg
Syracuse Orange
13 scored players
53.7
Avg
SMU Mustangs
11 scored players
52.8
Avg
Pittsburgh Panthers
11 scored players
52.7
Avg
Boston College Eagles
9 scored players
51.8
Avg
Top Athletes
Hannah Hidalgo
G · Notre Dame Fighting Irish
Kymora Johnson
G · Virginia Cavaliers
Toby Fournier
F · Duke Blue Devils
Uche Izoje
C · Syracuse Orange
Zamareya Jones
G · NC State Wolfpack
Zoe Brooks
G · NC State Wolfpack
Khamil Pierre
F · NC State Wolfpack
Mackenzie Nelson
G · Virginia Tech Hokies
Talayah Walker
G · Georgia Tech Yellow Jackets
Mia Moore
G · Clemson Tigers
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). We update scores after every Sunday's full sync.
Methodology note: women's basketball calibration is developing as the dataset grows. Treat scores as directional while the sample expands.
Read the full methodology →