| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Tri-City Americans | WHL | 9 | 1 | 1 | 2 | 0.222 | 0.1081 | 0.1266 | 0.5452 | 0.6384 |
| 2022-23 | Tri-City Americans | WHL | 62 | 22 | 32 | 54 | 0.871 | 0.4237 | 0.4764 | 2.1372 | 2.4029 |
| 2023-24 | Tri-City Americans | WHL | 68 | 23 | 45 | 68 | 1.000 | 0.4865 | 0.5230 | 2.4537 | 2.6378 |
| 2024-25 | Tri-City Americans | WHL | 68 | 21 | 36 | 57 | 0.838 | 0.4078 | 0.4166 | 2.0567 | 2.1011 |
| 2025-26 | Brandon Wheat Kings | WHL | 68 | 16 | 42 | 58 | 0.853 | 0.4149 | 0.4047 | 2.0928 | 2.0412 |
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.