| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Medicine Hat Tigers | WHL | 13 | 2 | 1 | 3 | 0.231 | 0.1123 | 0.1242 | 0.5638 | 0.6235 |
| 2022-23 | Medicine Hat Tigers | WHL | 68 | 1 | 8 | 9 | 0.132 | 0.0644 | 0.0682 | 0.3234 | 0.3426 |
| 2023-24 | Medicine Hat Tigers | WHL | 68 | 2 | 20 | 22 | 0.324 | 0.1574 | 0.1590 | 0.7902 | 0.7981 |
| 2024-25 | Medicine Hat Tigers | WHL | 50 | 3 | 24 | 27 | 0.540 | 0.2627 | 0.2513 | 1.3191 | 1.2618 |
| 2025-26 | Medicine Hat Tigers | WHL | 51 | 6 | 19 | 25 | 0.490 | 0.2385 | 0.2171 | 1.1974 | 1.0900 |
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.