| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Prince George Spruce Kings | BCHL | 37 | 5 | 8 | 13 | 0.351 | 0.1354 | 0.1354 | 0.5114 | 0.5114 |
| 2020-21 | Brooks Bandits | AJHL | 20 | 5 | 8 | 13 | 0.650 | 0.2180 | 0.2180 | 0.6015 | 0.6015 |
| 2021-22 | Brooks Bandits | AJHL | 60 | 57 | 82 | 139 | 2.317 | 0.7770 | 0.7404 | 2.1439 | 2.0428 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Western Michigan | D1 | NCHC | — | 39 | 13 | 36 | 49 | 1.256 |
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.