| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Surrey Eagles | BCHL | 58 | 8 | 23 | 31 | 0.534 | 0.2059 | 0.2091 | 0.7779 | 0.7902 |
| 2019-20 | Bonnyville Pontiacs | AJHL | 57 | 24 | 61 | 85 | 1.491 | 0.5001 | 0.5001 | 1.3800 | 1.3800 |
| 2020-21 | Bonnyville Pontiacs | AJHL | 4 | 2 | 0 | 2 | 0.500 | 0.1677 | 0.1677 | 0.4627 | 0.4627 |
| 2022-23 | Acadia Univ. | USports-M | 9 | 1 | 0 | 1 | 0.111 | 0.0586 | 0.0598 | 0.3256 | 0.3323 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Alaska Fairbanks | D1 | WCHA | — | 6 | 0 | 1 | 1 | 0.167 |
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.