| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Canmore Eagles | AJHL | 39 | 4 | 17 | 21 | 0.538 | 0.1787 | 0.1989 | 0.4991 | 0.5555 |
| 2023-24 | Fargo Force | USHL | 51 | 2 | 10 | 12 | 0.235 | 0.1446 | 0.1507 | 0.6932 | 0.7222 |
| 2024-25 | Muskegon Lumberjacks | USHL | 59 | 6 | 19 | 25 | 0.424 | 0.2604 | 0.2580 | 1.2483 | 1.2369 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Minnesota | D1 | BigTen | FR | 31 | 0 | 1 | 1 | 0.032 |
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.