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 | Bloomington Jefferson High (W) | USHS-MN-W | 7 | 1 | 0 | 1 | 0.143 | 0.0216 | 0.0216 |
| 2015-16 | Bloomington Jefferson High (W) | USHS-MN-W | 16 | 1 | 3 | 4 | 0.250 | 0.0377 | 0.0377 |
| 2016-17 | Bloomington Jefferson High (W) | USHS-MN-W | 24 | 14 | 6 | 20 | 0.833 | 0.1258 | 0.1258 |
| 2017-18 | Bloomington Jefferson High (W) | USHS-MN-W | 24 | 18 | 17 | 35 | 1.458 | 0.2202 | 0.2202 |
| 2018-19 | Bloomington Jefferson High (W) | USHS-MN-W | 25 | 9 | 14 | 23 | 0.920 | 0.1389 | 0.1389 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2019-20 | Nazareth | UCHC | FR | 23 | 6 | 14 | 20 | 0.870 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| 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 |
| 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 |
| Amanda Bäckebo | SDHL · 2012-13 · 0.11 PPG | 0.056 | Syracuse |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Adrienne Hansen | 2023-24 · 0.70 PPG | 0.481 | Wisconsin-Eau Claire | WIAC |
| Lauren Schmidt | 2024-25 · 1.00 PPG | 0.333 | St. Catherine | MIAC |
| Alyson Vogelsang | 2023-24 · 0.81 PPG | — | St. Catherine | MIAC |
| Andrea Noss | 2013-14 · 0.52 PPG | 0.667 | SUNY Oswego | SUNYAC |
| Jana Lesch | 2023-24 · 1.44 PPG | 0.222 | 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.