| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Humboldt Broncos | SJHL | 52 | 5 | 24 | 29 | 0.558 | 0.1429 | 0.1646 | 0.4204 | 0.4844 |
| 2023-24 | Langley Rivermen | BCHL | 54 | 2 | 23 | 25 | 0.463 | 0.1784 | 0.1950 | 0.6738 | 0.7365 |
| 2024-25 | Langley Rivermen | BCHL | 24 | 2 | 7 | 9 | 0.375 | 0.1445 | 0.1507 | 0.5457 | 0.5690 |
| 2025-26 | Victoria Royals | WHL | 6 | 0 | 0 | 0 | 0.000 | — | — | — | — |
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.