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 | Minneapolis High (W) | USHS-MN-W | 25 | 14 | 2 | 16 | 0.640 | 0.0966 | 0.0966 |
| 2020-21 | Minneapolis High (W) | USHS-MN-W | 18 | 12 | 8 | 20 | 1.111 | 0.1678 | 0.1678 |
| 2021-22 | Benilde-St. Margaret's (W) | USHS-MN-W | 15 | 3 | 4 | 7 | 0.467 | 0.0705 | 0.0705 |
| 2022-23 | Benilde-St. Margaret's (W) | USHS-MN-W | 26 | 16 | 9 | 25 | 0.962 | 0.1452 | 0.1410 |
| 2023-24 | Benilde-St. Margaret's (W) | USHS-MN-W | 27 | 12 | 11 | 23 | 0.852 | 0.1286 | 0.1195 |
| Season | School | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Colby | NESCAC | SO | 20 | 3 | 3 | 6 | 0.300 |
| 2024-25 | Colby | NESCAC | FR | 19 | 2 | 4 | 6 | 0.316 |
| Player | League · Season · PPG | FR College PPG | School |
|---|---|---|---|
| Tianna Gunderson | USHS-MN-W · 2012-13 · 0.79 PPG | 0.069 | Minnesota |
| Renee Saltness | USHS-MN-W · 2012-13 · 0.79 PPG | 0.029 | Quinnipiac |
| Rebecca Lindblad | USHS-W · 2013-14 · 1.43 PPG | 0.057 | UConn |
| Janna Haeg | USHS-MN-W · 2012-13 · 0.76 PPG | 0.303 | St. Cloud State |
| Kendall Williamson | USHS-MN-W · 2012-13 · 0.76 PPG | 0.000 | Colgate |
| Player | Junior Season · PPG | FR College PPG | School | Conference |
|---|---|---|---|---|
| Sydney Mintz | 2022-23 · 0.38 PPG | 0.750 | Utica | UCHC |
| Skyler Arneson | 2022-23 · 0.70 PPG | — | Wisconsin-Stevens Point | WIAC |
| Allie LeClaire | 2022-23 · 0.88 PPG | 0.333 | Wisconsin-Eau Claire | WIAC |
| Bella Schmidt | 2022-23 · 1.00 PPG | 0.292 | Suffolk | NEHC |
| Annabel Mehta | 2022-23 · 0.42 PPG | 0.654 | Hamline | 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.