| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Rivers School | NE-Prep | 23 | 1 | 1 | 2 | 0.087 | 0.0172 | 0.0172 | 0.0396 | 0.0396 |
| 2023-24 | Rivers School | NE-Prep | 30 | 4 | 14 | 18 | 0.600 | 0.1189 | 0.1189 | 0.2734 | 0.2734 |
| 2024-25 | Rivers School | NE-Prep | 28 | 2 | 20 | 22 | 0.786 | 0.1556 | 0.1556 | 0.3580 | 0.3580 |
| 2025-26 | Québec Remparts | QMJHL | 58 | 2 | 15 | 17 | 0.293 | 0.1440 | 0.1482 | 0.7827 | 0.8058 |
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.