| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Chicago Steel | USHL | 27 | 1 | 2 | 3 | 0.111 | 0.0655 | 0.0699 | 0.3337 | 0.3562 |
| 2022-23 | Bismarck Bobcats | NAHL | 57 | 13 | 26 | 39 | 0.684 | 0.2514 | 0.2662 | 0.7222 | 0.7648 |
| 2023-24 | Bismarck Bobcats | NAHL | 56 | 19 | 34 | 53 | 0.946 | 0.3477 | 0.3516 | 0.9989 | 1.0100 |
| 2024-25 | Bismarck Bobcats | NAHL | 53 | 11 | 20 | 31 | 0.585 | 0.2149 | 0.2060 | 0.6174 | 0.5919 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Norbert | D3 | NCHA | FR | 0 | 0 | 0 | 0 | 0.000 |
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.