| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | NAHA Red 16U | 16U-AAA-W | 64 | 1 | 24 | 25 | 0.391 | 0.1751 | 0.1751 | — | — |
| 2015-16 | NAHA White 19U AAA | JWHL-U19 | 26 | 3 | 5 | 8 | 0.308 | 0.1155 | 0.1155 | — | — |
| 2016-17 | NAHA White 19U AAA | JWHL-U19 | 19 | 0 | 4 | 4 | 0.210 | 0.0790 | 0.0790 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Colby | D3 | NESCAC | — | 23 | 1 | 5 | 6 | 0.261 |
| 2022-23 | Colby | D3 | NESCAC | — | 26 | 4 | 12 | 16 | 0.615 |
| 2021-22 | Colby | D3 | NESCAC | — | 16 | 3 | 10 | 13 | 0.812 |
| 2020-21 | Colby | D3 | NESCAC | — | 0 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Colby | D3 | NESCAC | — | 18 | 0 | 7 | 7 | 0.389 |
| 2018-19 | Colby | D3 | NESCAC | — | 18 | 1 | 5 | 6 | 0.333 |
| 2017-18 | Union | D1 | ECAC-W | — | 6 | 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.