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 |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Orono High | USHS-MN-W | 25 | 0 | 3 | 3 | 0.120 | 0.0181 | 0.0181 |
| 2019-20 | Orono High | USHS-MN-W | 25 | 5 | 9 | 14 | 0.560 | 0.0846 | 0.0846 |
| 2020-21 | Orono High | USHS-MN-W | 20 | 3 | 6 | 9 | 0.450 | 0.0679 | 0.0679 |
| 2021-22 | Orono High | USHS-MN-W | 29 | 11 | 15 | 26 | 0.897 | 0.1354 | 0.1354 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Benedict | MIAC | SR | 28 | 2 | 6 | 8 | 0.286 |
| 2024-25 | Saint Benedict | MIAC | JR | 25 | 5 | 7 | 12 | 0.480 |
| 2023-24 | Saint Benedict | MIAC | SO | 25 | 0 | 2 | 2 | 0.080 |
| 2022-23 | Saint Benedict | MIAC | FR | 22 | 0 | 4 | 4 | 0.182 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Vilma Tanskanen | SMLIIGA-W · 2012-13 · 0.35 PPG | 0.182 | North Dakota |
| Lydia Passolt | USHS-MN-W · 2012-13 · 0.89 PPG | 0.095 | Bemidji 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 |
| Amanda Bäckebo | SDHL · 2012-13 · 0.11 PPG | 0.056 | Syracuse |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Alyson Vogelsang | 2023-24 · 0.81 PPG | — | St. Catherine | MIAC |
| Lauren Schmidt | 2024-25 · 1.00 PPG | 0.333 | St. Catherine | MIAC |
| Adrienne Hansen | 2023-24 · 0.70 PPG | 0.481 | Wisconsin-Eau Claire | WIAC |
| Jana Lesch | 2023-24 · 1.44 PPG | 0.222 | Wisconsin-Eau Claire | WIAC |
| Ella Hansen | 2023-24 · 0.65 PPG | 0.500 | Wisconsin-Eau Claire | WIAC |
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.