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 |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Moose Lake Area High (W) | USHS-MN-W | 25 | 2 | 5 | 7 | 0.280 | 0.0423 | 0.0423 |
| 2020-21 | Moose Lake Area High (W) | USHS-MN-W | 19 | 2 | 4 | 6 | 0.316 | 0.0477 | 0.0477 |
| 2021-22 | Moose Lake Area High (W) | USHS-MN-W | 25 | 5 | 8 | 13 | 0.520 | 0.0785 | 0.0785 |
| 2022-23 | Moose Lake Area High (W) | USHS-MN-W | 26 | 2 | 8 | 10 | 0.385 | 0.0581 | 0.0546 |
| 2023-24 | Moose Lake Area High (W) | USHS-MN-W | 27 | 6 | 21 | 27 | 1.000 | 0.1510 | 0.1357 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Benedict | MIAC | SO | 28 | 6 | 3 | 9 | 0.321 |
| 2024-25 | Saint Benedict | MIAC | FR | 25 | 3 | 3 | 6 | 0.240 |
| 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 |
| Ella Hansen | 2023-24 · 0.65 PPG | 0.500 | Wisconsin-Eau Claire | WIAC |
| Sam Mugge | 2015-16 · 0.80 PPG | — | Wisconsin-Superior | WIAC |
| Jana Lesch | 2023-24 · 1.44 PPG | 0.222 | Wisconsin-Eau Claire | WIAC |
| Emily Wendorf | 2022-23 · 0.74 PPG | 0.440 | Saint Benedict | MIAC |
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.