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 |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Rochester Lourdes High (W) | USHS-MN-W | 25 | 31 | 21 | 52 | 2.080 | 0.3141 | 0.3141 |
| 2018-19 | Rochester Lourdes High (W) | USHS-MN-W | 23 | 24 | 27 | 51 | 2.217 | 0.3348 | 0.3348 |
| 2019-20 | Rochester Lourdes High (W) | USHS-MN-W | 25 | 20 | 31 | 51 | 2.040 | 0.3080 | 0.3080 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2022-23 | Wisconsin-River Falls | WIAC | SO | 29 | 10 | 22 | 32 | 1.103 |
| 2021-22 | Wisconsin-River Falls | WIAC | FR | 24 | 12 | 4 | 16 | 0.667 |
| 2020-21 | Sacred Heart | NEWHA | FR | 0 | 0 | 0 | 0 | 0.000 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Jordan McLaughlin | USHS-MN-W · 2013-14 · 2.22 PPG | 0.294 | Minnesota State |
| Catherine Skaja | USHS-MN-W · 2013-14 · 2.21 PPG | 0.342 | Minnesota |
| Carly Bullock | USHS-MN-W · 2013-14 · 2.20 PPG | 0.812 | Princeton |
| Karlie Lund | USHS-MN-W · 2013-14 · 2.20 PPG | 1.182 | Princeton |
| Brooklynn Schugel | USHS-MN-W · 2013-14 · 2.26 PPG | 0.270 | Minnesota Duluth |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Elizabeth Tabaka | 2012-13 · 1.32 PPG | 0.615 | Augsburg | MIAC |
| Karleigh Wolkerstorfer | 2012-13 · 1.62 PPG | 0.500 | Wisconsin-River Falls | WIAC |
| Dani Kocina | 2012-13 · 1.40 PPG | 0.581 | Wisconsin-River Falls | WIAC |
| Madison Anderson | 2021-22 · 0.95 PPG | 0.852 | Norwich | NEHC |
| Drew Kopek | 2022-23 · 1.94 PPG | 0.417 | SUNY Cortland | SUNYAC |
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.