| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Charlottetown Islanders | QMJHL | 35 | 7 | 9 | 16 | 0.457 | 0.2246 | 0.2494 | 1.2206 | 1.3554 |
| 2023-24 | Charlottetown Islanders | QMJHL | 55 | 12 | 24 | 36 | 0.654 | 0.3216 | 0.3413 | 1.7477 | 1.8546 |
| 2024-25 | Charlottetown Islanders | QMJHL | 52 | 22 | 36 | 58 | 1.115 | 0.5480 | 0.5546 | 2.9785 | 3.0142 |
| 2025-26 | Charlottetown Islanders | QMJHL | 51 | 28 | 39 | 67 | 1.314 | 0.6454 | 0.6226 | 3.5080 | 3.3843 |
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.