| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Swan Valley Stampeders | MJHL | 33 | 7 | 4 | 11 | 0.333 | 0.0642 | 0.0669 | 0.2100 | 0.2189 |
| 2023-24 | — | MJHL | 55 | 13 | 10 | 23 | 0.418 | 0.0805 | 0.0797 | 0.2635 | 0.2609 |
| 2024-25 | Waywayseecappo Wolverines | MJHL | 44 | 14 | 13 | 27 | 0.614 | 0.1181 | 0.1104 | 0.3867 | 0.3616 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Augsburg | D3 | MIAC | SO | 19 | 0 | 5 | 5 | 0.263 |
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.