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 |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | MoDo Hockey | SDHL | 36 | 5 | 8 | 13 | 0.361 | 0.4223 | 0.4109 |
| 2024-25 | MoDo Hockey | SDHL | 33 | 10 | 6 | 16 | 0.485 | 0.5670 | 0.5282 |
| 2025-26 | Färjestad BK | SDHL | 35 | 3 | 10 | 13 | 0.371 | 0.4344 | 0.3881 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | Syracuse | CHA-W | GR | 36 | 9 | 19 | 28 | 0.778 |
| 2021-22 | Syracuse | CHA-W | SR | 32 | 8 | 14 | 22 | 0.688 |
| 2020-21 | Syracuse | CHA-W | JR | 21 | 5 | 15 | 20 | 0.952 |
| 2019-20 | Syracuse | CHA-W | SO | 36 | 9 | 10 | 19 | 0.528 |
| 2018-19 | Syracuse | CHA-W | FR | 38 | 7 | 13 | 20 | 0.526 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Katie Rooney | USHS-MN-W · 2012-13 · 2.52 PPG | 0.219 | RPI |
| Darby Dodds | USHS-MN-W · 2013-14 · 2.52 PPG | 0.000 | Lindenwood |
| Dana Rasmussen | USHS-MN-W · 2012-13 · 2.62 PPG | 0.167 | Ohio State |
| Corbin Boyd | USHS-MN-W · 2013-14 · 2.42 PPG | 0.269 | Minnesota State |
| Lauren Hespenheide | USHS-MN-W · 2012-13 · 2.40 PPG | 0.257 | St. Cloud State |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Madie Leidt | 2025-26 · 0.63 PPG | 0.964 | Middlebury | NESCAC |
| Shannon Stewart | 2015-16 · 0.74 PPG | 0.833 | SUNY Plattsburgh | SUNYAC |
| Nina Hudakova | 2023-24 · 0.79 PPG | 0.962 | Wilkes | UCHC |
| Paige Lysne | 2010-11 · 1.84 PPG | — | Wisconsin-Eau Claire | WIAC |
| Alexis Peterson | 2013-14 · 1.55 PPG | 0.476 | Marian | 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.