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 |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Québec As M18 AAA | QMAAA-W | 1 | 0 | 0 | 0 | 0.000 | N/A | N/A |
| 2020-21 | Québec As M18 AAA | QMAAA-W | 0 | 0 | 0 | 0 | 0.000 | N/A | N/A |
| 2021-22 | Québec As M18 AAA | QMAAA-W | 27 | 14 | 7 | 21 | 0.778 | 0.1136 | 0.1108 |
| 2022-23 | Cégep Limoilou Titans | QCHL-W | 28 | 7 | 4 | 11 | 0.393 | 0.1066 | 0.1111 |
| 2023-24 | Cégep Limoilou Titans | QCHL-W | 30 | 15 | 10 | 25 | 0.833 | 0.2262 | 0.2254 |
| 2024-25 | Cégep Limoilou Titans | QCHL-W | 30 | 25 | 24 | 49 | 1.633 | 0.4433 | 0.4193 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Cloud State | WCHA-W | FR | 37 | 7 | 6 | 13 | 0.351 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Lauren Abbenante | NE-Prep-Girls · 2012-13 · 1.30 PPG | 0.607 | Holy Cross |
| Reagan Haley | USHS-MN-W · 2013-14 · 2.80 PPG | 0.108 | Minnesota Duluth |
| Haley Mack | USHS-MN-W · 2013-14 · 2.88 PPG | 0.371 | Bemidji State |
| Dana Rasmussen | USHS-MN-W · 2012-13 · 2.62 PPG | 0.167 | Ohio State |
| Phoebe Staenz | NE-Prep-Girls · 2012-13 · 1.38 PPG | 0.680 | Yale |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Lauren Smith | 2014-15 · 2.43 PPG | 0.577 | Wisconsin-Stevens Point | WIAC |
| Michaela O'Connor | 2016-17 · 4.25 PPG | 0.333 | Williams | NESCAC |
| Julia Masotta | 2017-18 · 1.16 PPG | 1.222 | Norwich | NEHC |
| Courtney Moriarty | 2012-13 · 1.11 PPG | 1.259 | SUNY Plattsburgh | SUNYAC |
| Emma Peterson | 2013-14 · 2.52 PPG | 0.552 | Wisconsin-Eau Claire | WIAC |
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.