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 | Devils Lake High | USHS-W | 14 | 0 | 0 | 0 | 0.000 | N/A | N/A |
| 2019-20 | Devils Lake High | USHS-W | 26 | 14 | 16 | 30 | 1.154 | 0.0980 | 0.0980 |
| 2020-21 | Devils Lake High | USHS-W | 17 | 8 | 5 | 13 | 0.765 | 0.0649 | 0.0649 |
| 2021-22 | Devils Lake High | USHS-W | 17 | 19 | 4 | 23 | 1.353 | 0.1149 | 0.1149 |
| 2022-23 | Devils Lake High | USHS-W | 23 | 45 | 10 | 55 | 2.391 | 0.2030 | 0.2030 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Hamline | MIAC | SO | 28 | 13 | 15 | 28 | 1.000 |
| 2024-25 | Hamline | MIAC | FR | 26 | 12 | 12 | 24 | 0.923 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Sylvia Marolt | USHS-MN-W · 2013-14 · 1.35 PPG | 0.000 | Bemidji State |
| Casey Leveillee | NE-Prep-Girls · 2012-13 · 0.63 PPG | 0.265 | Vermont |
| Natalie Snodgrass | USHS-MN-W · 2013-14 · 1.33 PPG | 1.000 | UConn |
| Sena Hanson | USHS-MN-W · 2012-13 · 1.36 PPG | 0.630 | Brown |
| Savannah Quandt | USHS-MN-W · 2012-13 · 1.36 PPG | 0.111 | Minnesota |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Jenna Allen | 2023-24 · 0.93 PPG | 0.586 | Augsburg | MIAC |
| Grace Karakas | 2023-24 · 1.38 PPG | 0.417 | SUNY Cortland | SUNYAC |
| Lauryn Hull | 2016-17 · 0.92 PPG | 0.607 | St. Scholastica | NCHA |
| Karleigh Wolkerstorfer | 2011-12 · 1.12 PPG | 0.500 | Wisconsin-River Falls | WIAC |
| Brionna Stafne | 2013-14 · 0.64 PPG | 0.875 | Bethel | 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.