| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USHL | 48 | 2 | 5 | 7 | 0.146 | 0.0860 | 0.0874 | 0.4296 | 0.4368 |
| 2022-23 | Madison Capitols | USHL | 12 | 1 | 1 | 2 | 0.167 | 0.0983 | 0.0948 | 0.4911 | 0.4738 |
| 2023-24 | Langley Rivermen | BCHL | 35 | 3 | 5 | 8 | 0.229 | 0.0881 | 0.0829 | 0.3331 | 0.3135 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Augsburg | D3 | MIAC | JR | 25 | 7 | 17 | 24 | 0.960 |
| 2024-25 | Augsburg | D3 | MIAC | — | 25 | 5 | 11 | 16 | 0.640 |
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.