| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Calgary Canucks | AJHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2019-20 | Drayton Valley Thunder | AJHL | 44 | 5 | 14 | 19 | 0.432 | 0.1448 | 0.1448 | 0.3996 | 0.3996 |
| 2020-21 | Drayton Valley Thunder | AJHL | 15 | 9 | 9 | 18 | 1.200 | 0.4025 | 0.4025 | 1.1105 | 1.1105 |
| 2021-22 | — | AJHL | 41 | 10 | 12 | 22 | 0.537 | 0.1800 | 0.1674 | 0.4966 | 0.4618 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Salve Regina | D3 | CNE | — | 18 | 1 | 3 | 4 | 0.222 |
| 2022-23 | Salve Regina | D3 | CNE | — | 24 | 7 | 9 | 16 | 0.667 |
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.