| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Houston Bulls | NAHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Corpus Christi IceRays | NAHL | 17 | 0 | 1 | 1 | 0.059 | 0.0209 | 0.0205 | 0.0617 | 0.0604 |
| 2023-24 | Rockland Nationals | CCHL | 17 | 0 | 4 | 4 | 0.235 | 0.0510 | 0.0463 | 0.1821 | 0.1652 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Elmira | D3 | UCHC | SO | 21 | 1 | 0 | 1 | 0.048 |
| 2024-25 | Elmira | D3 | UCHC | — | 11 | 0 | 1 | 1 | 0.091 |
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.