| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Drayton Valley Thunder | AJHL | 26 | 1 | 3 | 4 | 0.154 | 0.0516 | 0.0584 | 0.1423 | 0.1612 |
| 2022-23 | Drayton Valley Thunder | AJHL | 45 | 2 | 13 | 15 | 0.333 | 0.1118 | 0.1211 | 0.3084 | 0.3341 |
| 2023-24 | Okotoks Oilers | AJHL | 31 | 6 | 9 | 15 | 0.484 | 0.1623 | 0.1682 | 0.4478 | 0.4639 |
| 2024-25 | Calgary Canucks | AJHL | 52 | 28 | 26 | 54 | 1.038 | 0.3483 | 0.3424 | 0.9610 | 0.9446 |
| 2025-26 | Nanaimo Clippers | BCHL | 53 | 26 | 28 | 54 | 1.019 | 0.3926 | 0.3734 | 1.4828 | 1.4102 |
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.