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 | Shakopee High (women) | USHS-MN-W | 24 | 0 | 1 | 1 | 0.042 | 0.0063 | 0.0063 |
| 2019-20 | Shakopee High (women) | USHS-MN-W | 25 | 1 | 2 | 3 | 0.120 | 0.0181 | 0.0181 |
| 2020-21 | Shakopee High (women) | USHS-MN-W | 17 | 3 | 5 | 8 | 0.471 | 0.0711 | 0.0711 |
| 2021-22 | Shakopee High (women) | USHS-MN-W | 27 | 10 | 7 | 17 | 0.630 | 0.0951 | 0.0951 |
| 2022-23 | Shakopee High (women) | USHS-MN-W | 26 | 14 | 14 | 28 | 1.077 | 0.1626 | 0.1626 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | Gustavus Adolphus | MIAC | SO | 19 | 1 | 2 | 3 | 0.158 |
| 2023-24 | Gustavus Adolphus | MIAC | FR | 10 | 0 | 0 | 0 | 0.000 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Grace Zumwinkle | USHS-MN-W · 2012-13 · 1.08 PPG | 1.000 | Minnesota |
| Jordan Chancellor | USHS-MN-W · 2012-13 · 1.08 PPG | 0.517 | Yale |
| Jessica Bonfe | USHS-MN-W · 2013-14 · 1.08 PPG | 0.206 | Merrimack |
| Paetyn Levis | USHS-MN-W · 2013-14 · 1.08 PPG | 0.176 | Ohio State |
| Ivy Dynek | USHS-W · 2012-13 · 1.92 PPG | 0.000 | St. Cloud State |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Delaney Kingsland | 2018-19 · 0.71 PPG | 0.556 | Lawrence | NCHA |
| Reilly Springman | 2014-15 · 0.62 PPG | 0.630 | Wisconsin-River Falls | WIAC |
| Kimberly Patterson | 2013-14 · 1.44 PPG | 0.273 | Saint Benedict | MIAC |
| Maddie McCollins | 2018-19 · 1.04 PPG | 0.379 | Wisconsin-River Falls | WIAC |
| Delaney Carle | 2013-14 · 1.14 PPG | 0.346 | Nazareth | UCHC |
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.