| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Charlottetown Islanders | QMJHL | 68 | 6 | 23 | 29 | 0.426 | 0.2095 | 0.2296 | 1.1389 | 1.2483 |
| 2023-24 | Charlottetown Islanders | QMJHL | 68 | 7 | 42 | 49 | 0.721 | 0.3540 | 0.3706 | 1.9242 | 2.0142 |
| 2024-25 | Charlottetown Islanders | QMJHL | 46 | 7 | 21 | 28 | 0.609 | 0.2991 | 0.2984 | 1.6254 | 1.6216 |
| 2025-26 | Charlottetown Islanders | QMJHL | 62 | 15 | 40 | 55 | 0.887 | 0.4358 | 0.4142 | 2.3688 | 2.2512 |
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.