| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | QMJHL | 55 | 28 | 20 | 48 | 0.873 | 0.4339 | 0.4857 | 2.3275 | 2.6056 |
| 2023-24 | Baie-Comeau Drakkar | QMJHL | 68 | 51 | 31 | 82 | 1.206 | 0.5996 | 0.6417 | 3.2161 | 3.4419 |
| 2024-25 | Baie-Comeau Drakkar | QMJHL | 58 | 43 | 37 | 80 | 1.379 | 0.6858 | 0.7002 | 3.6786 | 3.7560 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Maine | D1 | HockeyEast | FR | 27 | 18 | 11 | 29 | 1.074 |
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.