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 | Northern Lakes Lightning | USHS-MN-W | 24 | 5 | 4 | 9 | 0.375 | 0.0566 | 0.0566 |
| 2019-20 | Northern Lakes Lightning | USHS-MN-W | 25 | 7 | 10 | 17 | 0.680 | 0.1027 | 0.1027 |
| 2020-21 | Northern Lakes Lightning | USHS-MN-W | 20 | 12 | 13 | 25 | 1.250 | 0.1888 | 0.1888 |
| 2021-22 | Northern Lakes Lightning | USHS-MN-W | 27 | 26 | 17 | 43 | 1.593 | 0.2405 | 0.2405 |
| 2022-23 | Northern Lakes Lightning | USHS-MN-W | 25 | 36 | 16 | 52 | 2.080 | 0.3141 | 0.2905 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Gustavus Adolphus | MIAC | FR | 5 | 0 | 0 | 0 | 0.000 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Lindsay Roethke | USHS-MN-W · 2012-13 · 1.96 PPG | 0.027 | UConn |
| Lynn Astrup | USHS-MN-W · 2013-14 · 2.04 PPG | 0.081 | Minnesota Duluth |
| Liz Schepers | USHS-MN-W · 2013-14 · 1.84 PPG | 0.410 | Ohio State |
| Emily Bergland | USHS-MN-W · 2013-14 · 2.04 PPG | 0.114 | Bemidji State |
| Alev Baysoy | USHS-MN-W · 2013-14 · 1.86 PPG | 0.000 | Princeton |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Madison Kadrlik | 2022-23 · 1.08 PPG | 0.643 | Wisconsin-River Falls | WIAC |
| Molly Pohlkamp | 2022-23 · 0.78 PPG | 0.920 | Wisconsin-Stevens Point | WIAC |
| Kaiya Sandy | 2024-25 · 1.27 PPG | 0.571 | Hamline | MIAC |
| Annalee Holzer | 2023-24 · 1.37 PPG | 0.500 | St. Norbert | NCHA |
| Abby Hansberger | 2024-25 · 0.40 PPG | 1.643 | Concordia (WI) | NCHA |
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.