| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Vernon Vipers | BCHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Okotoks Oilers | AJHL | 9 | 3 | 2 | 5 | 0.556 | 0.1863 | 0.2069 | 0.5142 | 0.5709 |
| 2023-24 | Calgary Canucks | AJHL | 52 | 17 | 26 | 43 | 0.827 | 0.2773 | 0.2948 | 0.7652 | 0.8135 |
| 2024-25 | Tri-City Americans | WHL | 54 | 21 | 21 | 42 | 0.778 | 0.3784 | 0.3722 | 1.9085 | 1.8771 |
| 2025-26 | Tri-City Americans | WHL | 68 | 16 | 31 | 47 | 0.691 | 0.3363 | 0.3152 | 1.6960 | 1.5896 |
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.