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 | Williamsville Federation | USHS-W | 7 | 0 | 1 | 1 | 0.143 | 0.0121 | 0.0121 |
| 2018-19 | Williamsville Federation | USHS-W | 14 | 1 | 0 | 1 | 0.071 | 0.0061 | 0.0061 |
| 2019-20 | Williamsville Federation | USHS-W | 10 | 8 | 6 | 14 | 1.400 | 0.1189 | 0.1189 |
| 2020-21 | Williamsville Federation | USHS-W | 16 | 23 | 9 | 32 | 2.000 | 0.1698 | 0.1698 |
| 2021-22 | Williamsville Federation | USHS-W | 16 | 23 | 9 | 32 | 2.000 | 0.1698 | 0.1698 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | SUNY Plattsburgh | SUNYAC | SO | 28 | 4 | 6 | 10 | 0.357 |
| 2022-23 | SUNY Plattsburgh | SUNYAC | FR | 28 | 4 | 3 | 7 | 0.250 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Grace Bizal | USHS-MN-W · 2012-13 · 1.16 PPG | 0.268 | Boston College |
| Kate Hallett | USHS-MN-W · 2012-13 · 1.08 PPG | 0.100 | Harvard |
| Katie Robinson | USHS-MN-W · 2012-13 · 1.08 PPG | 0.129 | Minnesota |
| Lauren Boyle | USHS-MN-W · 2013-14 · 1.08 PPG | 0.486 | Ohio State |
| Kendra Nealey | USHS-W · 2013-14 · 2.14 PPG | 0.212 | Cornell |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Avery Engbrecht | 2023-24 · 1.27 PPG | 0.370 | Wisconsin-Stevens Point | WIAC |
| Kylie Scott | 2022-23 · 1.04 PPG | 0.440 | Gustavus Adolphus | MIAC |
| Abby Reule | 2018-19 · 1.04 PPG | 0.450 | Concordia | MIAC |
| Lindsey Hays | 2016-17 · 1.12 PPG | 0.417 | St. Catherine | MIAC |
| Emily Lemker | 2018-19 · 1.12 PPG | 0.417 | Saint Benedict | 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.