| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Camrose Kodiaks | AJHL | 8 | 1 | 1 | 2 | 0.250 | 0.0838 | 0.0838 | 0.2314 | 0.2314 |
| 2021-22 | Calgary Canucks | AJHL | 60 | 20 | 31 | 51 | 0.850 | 0.2851 | 0.2843 | 0.7866 | 0.7843 |
| 2022-23 | Calgary Canucks | AJHL | 60 | 29 | 35 | 64 | 1.067 | 0.3578 | 0.3390 | 0.9871 | 0.9353 |
| 2025-26 | Univ. of Guelph | USports-M | 19 | 4 | 2 | 6 | 0.316 | 0.1666 | 0.1662 | 0.9256 | 0.9235 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Stonehill | D1 | AHA | — | 24 | 4 | 3 | 7 | 0.292 |
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.