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 |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Buffalo High | USHS-MN-W | 25 | 14 | 6 | 20 | 0.800 | 0.1208 | 0.1208 |
| 2017-18 | Buffalo High | USHS-MN-W | 25 | 33 | 15 | 48 | 1.920 | 0.2899 | 0.2899 |
| 2018-19 | Buffalo High | USHS-MN-W | 25 | 24 | 21 | 45 | 1.800 | 0.2718 | 0.2718 |
| 2019-20 | Buffalo High | USHS-MN-W | 25 | 27 | 20 | 47 | 1.880 | 0.2839 | 0.2839 |
| 2025-26 | Seattle Torrent | PWHL | 11 | 1 | 0 | 1 | 0.091 | N/A | N/A |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | UConn | HEA-W | GR | 36 | 16 | 6 | 22 | 0.611 |
| 2023-24 | UConn | HEA-W | SR | 38 | 17 | 11 | 28 | 0.737 |
| 2022-23 | UConn | HEA-W | JR | 35 | 13 | 7 | 20 | 0.571 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Liz Schepers | USHS-MN-W · 2013-14 · 1.84 PPG | 0.410 | Ohio State |
| Paige Voight | USHS-MN-W · 2013-14 · 1.76 PPG | 0.559 | Merrimack |
| Amy Petersen | USHS-MN-W · 2012-13 · 1.92 PPG | 0.784 | Penn State |
| Mariah Gardner | USHS-MN-W · 2013-14 · 1.74 PPG | 0.071 | Minnesota State |
| Emily Gunderson | USHS-MN-W · 2012-13 · 1.71 PPG | 0.171 | Lindenwood |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Marta Mazzocchi | 2022-23 · 0.90 PPG | 0.727 | Trinity | NESCAC |
| Rylan Kissel | 2024-25 · 1.11 PPG | 0.577 | Bethel | MIAC |
| Morgan Mordini | 2017-18 · 1.78 PPG | 0.370 | Elmira | UCHC |
| Hattie Verstegen | 2018-19 · 1.48 PPG | 0.444 | Wisconsin-Eau Claire | WIAC |
| Riley Schneider | 2014-15 · 1.52 PPG | 0.435 | 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.