| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | WHL | 6 | 0 | 1 | 1 | 0.167 | 0.0811 | 0.0929 | 0.4090 | 0.4686 |
| 2023-24 | Kamloops Blazers | WHL | 68 | 12 | 19 | 31 | 0.456 | 0.2218 | 0.2432 | 1.1186 | 1.2264 |
| 2024-25 | Kamloops Blazers | WHL | 59 | 31 | 35 | 66 | 1.119 | 0.5442 | 0.5676 | 2.7447 | 2.8626 |
| 2025-26 | Kamloops Blazers | WHL | 67 | 38 | 48 | 86 | 1.284 | 0.6245 | 0.6224 | 3.1496 | 3.1391 |
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.