Based on 40 comparable players
Most women's college players come directly from high school hockey. Junior or HS season stats below (when available on Elite Prospects).
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-W PPG | Age-Adjusted |
|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Team Colorado 19U AAA | JWHL-U19 | 24 | 4 | 2 | 6 | 0.250 | 0.0970 | 0.0970 |
| 2022-23 | Göteborg HC | SDHL | 13 | 1 | 1 | 2 | 0.154 | 0.1799 | 0.1738 |
| 2023-24 | AIK | SDHL | 36 | 3 | 2 | 5 | 0.139 | 0.1624 | 0.1450 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2021-22 | Utica | UCHC | — | 27 | 18 | 12 | 30 | 1.111 |
| 2020-21 | Utica | UCHC | GR | 13 | 2 | 2 | 4 | 0.308 |
| 2019-20 | Utica | UCHC | SR | 4 | 0 | 2 | 2 | 0.500 |
| 2018-19 | Utica | UCHC | JR | 26 | 12 | 8 | 20 | 0.769 |
| 2017-18 | Utica | UCHC | SO | 27 | 6 | 17 | 23 | 0.852 |
| 2016-17 | Norwich | NEHC | FR | 9 | 0 | 0 | 0 | 0.000 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Ivy Dynek | USHS-W · 2013-14 · 1.78 PPG | 0.000 | St. Cloud State |
| Carly Bullock | USHS-MN-W · 2012-13 · 0.92 PPG | 0.812 | Princeton |
| Emily Antony | USHS-MN-W · 2012-13 · 0.92 PPG | 0.444 | Minnesota State |
| Katie Detert | USHS-W · 2012-13 · 1.80 PPG | 0.000 | St. Cloud State |
| Vilma Tanskanen | SMLIIGA-W · 2012-13 · 0.35 PPG | 0.182 | North Dakota |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Megan Delay | 2021-22 · 0.50 PPG | 0.458 | SUNY Plattsburgh | SUNYAC |
| Ann-Frédérique Guay | 2024-25 · 0.31 PPG | 1.103 | Norwich | NEHC |
| Meg Aiken | 2025-26 · 0.64 PPG | 0.476 | Castleton | NEHC |
| Mae Olshansky | 2025-26 · 0.35 PPG | — | SUNY Plattsburgh | SUNYAC |
| Olivia Stewart | 2025-26 · 0.34 PPG | 0.519 | Southern Maine | NEHC |
Women's college hockey projections draw primarily on high school and junior stats when available. Because most women go directly from HS to college, projections with limited pre-college data use conference-based priors.
NCAAe-W factors are derived from historical pre-college→NCAA-W transitions. For many players, projection confidence is lower than men's due to sparse pre-college tracking.