| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | North Bay Battalion | OHL | 7 | 0 | 1 | 1 | 0.143 | 0.0827 | 0.0905 | 0.3672 | 0.4020 |
| 2022-23 | North Bay Battalion | OHL | 63 | 2 | 7 | 9 | 0.143 | 0.0827 | 0.0870 | 0.3672 | 0.3861 |
| 2023-24 | North Bay Battalion | OHL | 67 | 2 | 14 | 16 | 0.239 | 0.1381 | 0.1386 | 0.6136 | 0.6158 |
| 2024-25 | Windsor Spitfires | OHL | 65 | 3 | 17 | 20 | 0.308 | 0.1780 | 0.1695 | 0.7906 | 0.7527 |
| 2025-26 | Windsor Spitfires | OHL | 66 | 3 | 23 | 26 | 0.394 | 0.2279 | 0.2055 | 1.0121 | 0.9126 |
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.