| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | North York Rangers | OJHL | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | Kimball Union | NE-Prep | 36 | 6 | 8 | 14 | 0.389 | 0.0770 | 0.0770 | 0.1772 | 0.1772 |
| 2024-25 | Kimball Union | NE-Prep | 33 | 12 | 11 | 23 | 0.697 | 0.1381 | 0.1381 | 0.3176 | 0.3176 |
| 2025-26 | Toronto Patriots | OJHL | 16 | 4 | 6 | 10 | 0.625 | 0.1532 | 0.1490 | 0.4303 | 0.4185 |
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.