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 |
|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Kimball Union | NE-Prep-Girls | 23 | 5 | 5 | 10 | 0.430 | 0.1397 | 0.1397 |
| 2015-16 | Kimball Union | NE-Prep-Girls | 27 | 6 | 5 | 11 | 0.410 | 0.1332 | 0.1332 |
| 2016-17 | Kimball Union | NE-Prep-Girls | 23 | 1 | 3 | 4 | 0.170 | 0.0552 | 0.0552 |
| 2017-18 | Kimball Union | NE-Prep-Girls | 27 | 7 | 12 | 19 | 0.700 | 0.2274 | 0.2274 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2021-22 | Colby | NESCAC | SR | 14 | 1 | 4 | 5 | 0.357 |
| 2020-21 | Colby | NESCAC | JR | 2 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Colby | NESCAC | SO | 7 | 0 | 1 | 1 | 0.143 |
| 2018-19 | Colby | NESCAC | FR | 18 | 2 | 2 | 4 | 0.222 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| 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 |
| Taylor Wente | USHS-MN-W · 2013-14 · 1.54 PPG | 0.658 | Minnesota |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Avery Engbrecht | 2023-24 · 1.27 PPG | 0.370 | Wisconsin-Stevens Point | WIAC |
| Megan Dulong | 2014-15 · 1.17 PPG | 0.407 | Wisconsin-Superior | WIAC |
| Jessica Krysik | 2014-15 · 1.18 PPG | — | St. Olaf | MIAC |
| Hannah Gallivan | 2016-17 · 1.18 PPG | — | Buffalo State | SUNYAC |
| Courtney Moser | 2014-15 · 0.85 PPG | 0.560 | Saint Mary's (MN) | 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.