| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Madison Capitols | USHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Madison Capitols | USHL | 31 | 1 | 3 | 4 | 0.129 | 0.0793 | 0.0832 | 0.3801 | 0.3990 |
| 2023-24 | Waterloo Black Hawks | USHL | 56 | 4 | 14 | 18 | 0.321 | 0.1976 | 0.1976 | 0.9469 | 0.9469 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Penn State | D1 | BigTen | — | 25 | 1 | 3 | 4 | 0.160 |
| 2024-25 | Penn State | D1 | BigTen | — | 27 | 0 | 3 | 3 | 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.