| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Kamloops Blazers | WHL | 7 | 0 | 1 | 1 | 0.143 | 0.0695 | 0.0752 | 0.3506 | 0.3795 |
| 2022-23 | Kamloops Blazers | WHL | 60 | 3 | 9 | 12 | 0.200 | 0.0973 | 0.1008 | 0.4907 | 0.5083 |
| 2023-24 | Kamloops Blazers | WHL | 52 | 2 | 19 | 21 | 0.404 | 0.1964 | 0.1938 | 0.9908 | 0.9775 |
| 2024-25 | Kamloops Blazers | WHL | 45 | 2 | 12 | 14 | 0.311 | 0.1514 | 0.1413 | 0.7633 | 0.7123 |
| 2025-26 | Kamloops Blazers | WHL | 67 | 3 | 30 | 33 | 0.492 | 0.2396 | 0.2125 | 1.2084 | 1.0717 |
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.