| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Blake School (W) | USHS-MN-W | 24 | 5 | 11 | 16 | 0.667 | 0.1071 | 0.1071 | — | — |
| 2016-17 | Blake School (W) | USHS-MN-W | 25 | 16 | 21 | 37 | 1.480 | 0.2377 | 0.2377 | — | — |
| 2017-18 | Blake School (W) | USHS-MN-W | 25 | 14 | 22 | 36 | 1.440 | 0.2313 | 0.2313 | — | — |
| 2018-19 | Blake School (W) | USHS-MN-W | 25 | 30 | 32 | 62 | 2.480 | 0.3983 | 0.3983 | — | — |
| 2019-20 | Blake School (W) | USHS-MN-W | 25 | 41 | 27 | 68 | 2.720 | 0.4368 | 0.4368 | — | — |
| 2025-26 | Seattle Torrent | PWHL | 24 | 0 | 2 | 2 | 0.083 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Cornell | D1 | ECAC-W | GR | 35 | 12 | 10 | 22 | 0.629 |
| 2023-24 | Cornell | D1 | ECAC-W | SR | 34 | 16 | 18 | 34 | 1.000 |
| 2022-23 | Cornell | D1 | ECAC-W | JR | 27 | 11 | 16 | 27 | 1.000 |
| 2021-22 | Cornell | D1 | ECAC-W | SO | 29 | 14 | 13 | 27 | 0.931 |
| 2020-21 | Cornell | D1 | ECAC-W | FR | 0 | 0 | 0 | 0 | 0.000 |
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.