| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | NA3HL | 32 | 3 | 3 | 6 | 0.188 | 0.0235 | 0.0240 | 0.0592 | 0.0604 |
| 2022-23 | Elmira Impact | USPHL-Premier | 36 | 5 | 17 | 22 | 0.611 | 0.0799 | 0.0781 | 0.2074 | 0.2026 |
| 2023-24 | Elmira Impact | USPHL-Premier | 36 | 1 | 6 | 7 | 0.194 | 0.0254 | 0.0236 | 0.0660 | 0.0613 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Misericordia | D3 | MAC | — | 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.