| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Victoriaville Tigres | QMJHL | 4 | 0 | 1 | 1 | 0.250 | 0.1228 | 0.1362 | 0.6674 | 0.7402 |
| 2024-25 | Victoriaville Tigres | QMJHL | 61 | 3 | 16 | 19 | 0.311 | 0.1530 | 0.1622 | 0.8316 | 0.8814 |
| 2025-26 | Victoriaville Tigres | QMJHL | 59 | 1 | 19 | 20 | 0.339 | 0.1666 | 0.1687 | 0.9050 | 0.9164 |
| 2026-27 | Québec Remparts | QMJHL | 6 | 0 | 3 | 3 | 0.500 | 0.2457 | 0.2457 | 1.3348 | 1.3348 |
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.