| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Elliot Lake Vikings | NOJHL | 57 | 21 | 37 | 58 | 1.018 | 0.1699 | 0.1836 | 0.4236 | 0.4578 |
| 2023-24 | Toronto Patriots | OJHL | 52 | 13 | 12 | 25 | 0.481 | 0.1178 | 0.1209 | 0.3310 | 0.3398 |
| 2024-25 | Burlington Cougars | OJHL | 55 | 21 | 40 | 61 | 1.109 | 0.2718 | 0.2650 | 0.7636 | 0.7446 |
| 2025-26 | — | NAHL | 55 | 25 | 30 | 55 | 1.000 | 0.3674 | 0.3513 | 1.0555 | 1.0094 |
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.