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 | Moorhead High (W) | USHS-MN-W | 20 | 3 | 10 | 13 | 0.650 | 0.0982 | 0.0982 |
| 2021-22 | Moorhead High (W) | USHS-MN-W | 28 | 13 | 12 | 25 | 0.893 | 0.1348 | 0.1348 |
| 2022-23 | Moorhead High (W) | USHS-MN-W | 31 | 16 | 18 | 34 | 1.097 | 0.1656 | 0.1656 |
| 2023-24 | Moorhead High (W) | USHS-MN-W | 28 | 20 | 25 | 45 | 1.607 | 0.2427 | 0.2248 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2026-27 | Sacred Heart | NEWHA | JR | 0 | 0 | 0 | 0 | 0.000 |
| 2025-26 | Sacred Heart | NEWHA | SO | 36 | 7 | 7 | 14 | 0.389 |
| 2024-25 | Sacred Heart | NEWHA | FR | 38 | 9 | 6 | 15 | 0.395 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Jacqueline Kaasa | USHS-MN-W · 2013-14 · 1.46 PPG | 0.143 | Bemidji State |
| Lindsay Roethke | USHS-MN-W · 2013-14 · 1.52 PPG | 0.027 | UConn |
| Danielle Marmer | 19U-AAA-W · 2012-13 · 0.70 PPG | 0.108 | Quinnipiac |
| Sydney Brodt | USHS-MN-W · 2013-14 · 1.54 PPG | 0.600 | Minnesota Duluth |
| Brooklynn Schugel | USHS-MN-W · 2012-13 · 1.54 PPG | 0.270 | Minnesota Duluth |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Makenna Kadrlik | 2022-23 · 1.46 PPG | 0.375 | Wisconsin-River Falls | WIAC |
| Georgia Bailey | 2022-23 · 1.10 PPG | 0.500 | RPI | ECAC |
| Victoria Nelson | 2023-24 · 1.15 PPG | 0.480 | St. Scholastica | NCHA |
| Avery Engbrecht | 2022-23 · 1.44 PPG | 0.370 | Wisconsin-Stevens Point | WIAC |
| Mollie Koch | 2023-24 · 1.36 PPG | — | Saint Mary's | 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.