| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USHL | 6 | 1 | 1 | 2 | 0.333 | 0.2049 | 0.2203 | 0.9820 | 1.0558 |
| 2023-24 | Muskegon Lumberjacks | USHL | 59 | 1 | 13 | 14 | 0.237 | 0.1459 | 0.1496 | 0.6991 | 0.7169 |
| 2024-25 | Muskegon Lumberjacks | USHL | 58 | 1 | 6 | 7 | 0.121 | 0.0742 | 0.0723 | 0.3556 | 0.3465 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Thomas | D1 | CCHA | FR | 37 | 3 | 11 | 14 | 0.378 |
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.