| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Alaska All Stars 16U AAA | 16U-AAA-W | 39 | 2 | 4 | 6 | 0.154 | 0.0690 | 0.0706 | — | — |
| 2022-23 | NAHA Red 16U | 16U-AAA-W | 40 | 2 | 5 | 7 | 0.175 | 0.0785 | 0.0766 | — | — |
| 2023-24 | — | JWHL-U19 | 82 | 4 | 2 | 6 | 0.073 | 0.0275 | 0.0270 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Long Island Univ. | D1 | CHA-W | — | 2 | 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.