| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Philadelphia Jr Flyers 16U | 16U-AAA-W | 66 | 8 | 37 | 45 | 0.682 | 0.2747 | 0.2758 | — | — |
| 2023-24 | Philadelphia Jr Flyers 19U | 19U-AAA-W | 64 | 11 | 32 | 43 | 0.672 | 0.2321 | 0.2375 | — | — |
| 2024-25 | Philadelphia Jr Flyers 19U | JWHL-U19 | 21 | 9 | 18 | 27 | 1.286 | 0.4276 | 0.4151 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Penn State | D1 | WCHA-W | — | 36 | 1 | 3 | 4 | 0.111 |
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.