| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | QMJHL | 31 | 5 | 13 | 18 | 0.581 | 0.2852 | 0.2980 | 1.5504 | 1.6200 |
| 2023-24 | Chicoutimi Saguenéens | QMJHL | 59 | 4 | 38 | 42 | 0.712 | 0.3498 | 0.3483 | 1.9010 | 1.8926 |
| 2024-25 | Chicoutimi Saguenéens | QMJHL | 54 | 5 | 19 | 24 | 0.444 | 0.2183 | 0.2066 | 1.1867 | 1.1231 |
| 2025-26 | Chicoutimi Saguenéens | QMJHL | 62 | 12 | 28 | 40 | 0.645 | 0.3170 | 0.2850 | 1.7229 | 1.5491 |
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.