| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Seattle Thunderbirds | WHL | 11 | 1 | 1 | 2 | 0.182 | 0.0884 | 0.0975 | 0.4461 | 0.4921 |
| 2022-23 | — | WHL | 40 | 2 | 5 | 7 | 0.175 | 0.0851 | 0.0899 | 0.4294 | 0.4536 |
| 2023-24 | Everett Silvertips | WHL | 50 | 2 | 13 | 15 | 0.300 | 0.1459 | 0.1469 | 0.7361 | 0.7413 |
| 2024-25 | Kamloops Blazers | WHL | 56 | 1 | 12 | 13 | 0.232 | 0.1129 | 0.1077 | 0.5695 | 0.5431 |
| 2025-26 | Portland Winterhawks | WHL | 40 | 0 | 9 | 9 | 0.225 | 0.1095 | 0.0994 | 0.5521 | 0.5010 |
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.