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 |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Delano/Rockford High (women) | USHS-MN-W | 19 | 11 | 4 | 15 | 0.789 | 0.1192 | 0.1192 |
| 2021-22 | Benilde-St. Margaret's (W) | USHS-MN-W | 28 | 13 | 9 | 22 | 0.786 | 0.1186 | 0.1186 |
| 2022-23 | Benilde-St. Margaret's (W) | USHS-MN-W | 27 | 11 | 13 | 24 | 0.889 | 0.1342 | 0.1342 |
| 2023-24 | — | 16U-AAA-W | 6 | 0 | 3 | 3 | 0.500 | 0.1786 | 0.1786 |
| 2024-25 | Benilde-St. Margaret's (W) | USHS-MN-W | 27 | 21 | 17 | 38 | 1.407 | 0.2125 | 0.2125 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Minnesota State | CHA-W | FR | 25 | 0 | 2 | 2 | 0.080 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Katie Detert | USHS-W · 2013-14 · 2.50 PPG | 0.000 | St. Cloud State |
| Mariah Gardner | USHS-MN-W · 2012-13 · 1.40 PPG | 0.071 | Minnesota State |
| Abby Halluska | USHS-MN-W · 2013-14 · 1.40 PPG | 0.314 | Bemidji State |
| Gabby Billing | USHS-MN-W · 2013-14 · 1.40 PPG | 0.310 | Dartmouth |
| Charly Dalhquist | USHS-MN-W · 2013-14 · 1.40 PPG | 0.241 | North Dakota |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Gracyn Knowles | 2024-25 · 0.92 PPG | 0.548 | Wisconsin-River Falls | WIAC |
| Ella Konrad | 2024-25 · 0.74 PPG | 0.700 | Nazareth | UCHC |
| Brynn Puppe | 2015-16 · 0.92 PPG | 0.560 | Williams | NESCAC |
| Abby Pohlkamp | 2018-19 · 1.36 PPG | 0.379 | St. Scholastica | NCHA |
| Avery Olson | 2024-25 · 1.29 PPG | — | Connecticut College | NESCAC |
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.