| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Soo Greyhounds | OHL | 52 | 4 | 9 | 13 | 0.250 | 0.1446 | 0.1594 | 0.6424 | 0.7082 |
| 2023-24 | Soo Greyhounds | OHL | 66 | 12 | 14 | 26 | 0.394 | 0.2279 | 0.2403 | 1.0121 | 1.0673 |
| 2024-25 | Flint Firebirds | OHL | 68 | 16 | 29 | 45 | 0.662 | 0.3829 | 0.3840 | 1.7005 | 1.7055 |
| 2025-26 | Flint Firebirds | OHL | 47 | 24 | 31 | 55 | 1.170 | 0.6770 | 0.6449 | 3.0068 | 2.8644 |
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.