| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Breck School (W) | USHS-MN-W | 23 | 4 | 2 | 6 | 0.261 | 0.0419 | 0.0419 | — | — |
| 2017-18 | Breck School (W) | USHS-MN-W | 25 | 12 | 14 | 26 | 1.040 | 0.1670 | 0.1670 | — | — |
| 2018-19 | Breck School (W) | USHS-MN-W | 25 | 24 | 19 | 43 | 1.720 | 0.2762 | 0.2762 | — | — |
| 2019-20 | Breck School (W) | USHS-MN-W | 25 | 13 | 15 | 28 | 1.120 | 0.1799 | 0.1799 | — | — |
| 2020-21 | Breck School (W) | USHS-MN-W | 19 | 13 | 11 | 24 | 1.263 | 0.2029 | 0.2029 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Thomas | D1 | CHA-W | GR | 31 | 1 | 3 | 4 | 0.129 |
| 2024-25 | St. Thomas | D1 | CHA-W | SR | 36 | 4 | 4 | 8 | 0.222 |
| 2023-24 | Minnesota | D1 | WCHA-W | JR | 35 | 2 | 3 | 5 | 0.143 |
| 2022-23 | Minnesota | D1 | WCHA-W | SO | 17 | 0 | 2 | 2 | 0.118 |
| 2021-22 | Minnesota | D1 | WCHA-W | — | 8 | 0 | 2 | 2 | 0.250 |
| 2017-18 | Minnesota | D1 | WCHA-W | — | 38 | 5 | 8 | 13 | 0.342 |
| 2016-17 | Minnesota | D1 | WCHA-W | — | 38 | 3 | 5 | 8 | 0.211 |
| 2007-08 | Minnesota | D1 | WCHA-W | — | 2 | 0 | 0 | 0 | 0.000 |
| 2006-07 | Minnesota | D1 | WCHA-W | — | 36 | 0 | 0 | 0 | 0.000 |
| 2005-06 | Minnesota | D1 | WCHA-W | — | 41 | 1 | 1 | 2 | 0.049 |
How to read this: NCAAe and D3e factors convert a player's junior PPG into expected NCAA scoring at the D1 or D3 level. Harder conferences → lower projected PPG for the same player. A strong junior player (e.g. USHL 0.90 PPG) will project much higher in NESCAC than Big Ten because the D3 scoring environment is lower-difficulty.
Strength factor: conferences above 1.0 are harder than average; below 1.0 are easier. The formula is: Base NCAAe PPG ÷ Conference Strength = Projected PPG.