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 |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Delano/Rockford High (women) | USHS-MN-W | 25 | 18 | 22 | 40 | 1.600 | 0.2416 | 0.2416 |
| 2017-18 | Delano/Rockford High (women) | USHS-MN-W | 25 | 15 | 21 | 36 | 1.440 | 0.2174 | 0.2174 |
| 2018-19 | Delano/Rockford High (women) | USHS-MN-W | 25 | 20 | 17 | 37 | 1.480 | 0.2235 | 0.2235 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | Gustavus Adolphus | MIAC | GR | 27 | 6 | 12 | 18 | 0.667 |
| 2022-23 | Gustavus Adolphus | MIAC | SR | 30 | 7 | 23 | 30 | 1.000 |
| 2021-22 | Gustavus Adolphus | MIAC | JR | 27 | 14 | 15 | 29 | 1.074 |
| 2020-21 | Gustavus Adolphus | MIAC | SO | 5 | 0 | 1 | 1 | 0.200 |
| 2019-20 | Gustavus Adolphus | MIAC | FR | 25 | 8 | 2 | 10 | 0.400 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Jacqueline Kaasa | USHS-MN-W · 2013-14 · 1.46 PPG | 0.143 | Bemidji State |
| Danielle Marmer | 19U-AAA-W · 2012-13 · 0.70 PPG | 0.108 | Quinnipiac |
| Lindsay Roethke | USHS-MN-W · 2013-14 · 1.52 PPG | 0.027 | UConn |
| Aly Tremblay | USHS-W · 2012-13 · 2.61 PPG | 0.030 | RPI |
| Sydney Brodt | USHS-MN-W · 2013-14 · 1.54 PPG | 0.600 | Minnesota Duluth |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Jenna Allen | 2023-24 · 0.93 PPG | 0.586 | Augsburg | MIAC |
| Mia Montanari | 2024-25 · 1.08 PPG | 0.500 | RPI | ECAC |
| Flora Pasztor | 2025-26 · 1.35 PPG | — | Post | NE10 |
| Ellie Newpower | 2023-24 · 0.79 PPG | 0.679 | Hamline | MIAC |
| Taylor Lesnar | 2024-25 · 1.50 PPG | 0.357 | St. Norbert | 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.