| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Drumheller Dragons | AJHL | 43 | 4 | 10 | 14 | 0.326 | 0.1092 | 0.1154 | 0.3018 | 0.3190 |
| 2022-23 | Blackfalds Bulldogs | AJHL | 55 | 1 | 11 | 12 | 0.218 | 0.0732 | 0.0737 | 0.2022 | 0.2037 |
| 2023-24 | Drayton Valley Thunder | AJHL | 53 | 7 | 3 | 10 | 0.189 | 0.0633 | 0.0608 | 0.1749 | 0.1679 |
| 2024-25 | — | AJHL | 41 | 6 | 17 | 23 | 0.561 | 0.1882 | 0.1707 | 0.5199 | 0.4716 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Lawrence | D3 | NCHA | — | 21 | 3 | 1 | 4 | 0.191 |
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.