| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Milton Menace | OJHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | — | OJHL | 27 | 4 | 4 | 8 | 0.296 | 0.0726 | 0.0798 | 0.2040 | 0.2243 |
| 2023-24 | Burlington Cougars | OJHL | 43 | 3 | 2 | 5 | 0.116 | 0.0285 | 0.0299 | 0.0801 | 0.0839 |
| 2024-25 | Burlington Cougars | OJHL | 20 | 5 | 5 | 10 | 0.500 | 0.1226 | 0.1221 | 0.3443 | 0.3430 |
| 2025-26 | — | OJHL | 48 | 24 | 28 | 52 | 1.083 | 0.2655 | 0.2501 | 0.7459 | 0.7026 |
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.