| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Rouyn-Noranda Huskies | QMJHL | 54 | 8 | 9 | 17 | 0.315 | 0.1547 | 0.1621 | 0.8406 | 0.8810 |
| 2022-23 | Rouyn-Noranda Huskies | QMJHL | 60 | 2 | 11 | 13 | 0.217 | 0.1065 | 0.1064 | 0.5787 | 0.5782 |
| 2023-24 | Gatineau Olympiques | QMJHL | 68 | 38 | 41 | 79 | 1.162 | 0.5708 | 0.5422 | 3.1024 | 2.9468 |
| 2024-25 | Gatineau Olympiques | QMJHL | 63 | 35 | 31 | 66 | 1.048 | 0.5147 | 0.4636 | 2.7974 | 2.5196 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Bowling Green | D1 | CCHA | — | 33 | 5 | 5 | 10 | 0.303 |
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.