| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | St. Sebastian’s | NE-Prep | 16 | 1 | 0 | 1 | 0.062 | 0.0126 | 0.0126 | 0.0286 | 0.0286 |
| 2023-24 | St. Sebastian’s | NE-Prep | 28 | 9 | 5 | 14 | 0.500 | 0.1006 | 0.1006 | 0.2286 | 0.2286 |
| 2024-25 | U.S. National U18 Team | NTDP-U18 | 2 | 0 | 1 | 1 | 0.500 | 0.3716 | 0.3754 | 1.8749 | 1.8940 |
| 2025-26 | Moncton Wildcats | QMJHL | 54 | 21 | 17 | 38 | 0.704 | 0.3457 | 0.3595 | 1.8786 | 1.9535 |
| 2026-27 | Moncton Wildcats | QMJHL | 7 | 5 | 5 | 10 | 1.429 | 0.7019 | 0.7019 | 3.8138 | 3.8138 |
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.