| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Waterloo Black Hawks | USHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | Waterloo Black Hawks | USHL | 62 | 10 | 11 | 21 | 0.339 | 0.2082 | 0.2164 | 0.9979 | 1.0372 |
| 2022-23 | Waterloo Black Hawks | USHL | 62 | 11 | 30 | 41 | 0.661 | 0.4065 | 0.4014 | 1.9483 | 1.9237 |
| 2023-24 | Bloomington Jefferson | USHS-MN | 26 | 8 | 6 | 14 | 0.538 | 0.1450 | 0.1450 | 0.1308 | 0.1308 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan Tech | D1 | CCHA | — | 7 | 0 | 2 | 2 | 0.286 |
| 2024-25 | Michigan Tech | D1 | CCHA | — | 33 | 3 | 2 | 5 | 0.151 |
| 2023-24 | Michigan | D1 | BigTen | — | 7 | 1 | 1 | 2 | 0.286 |
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.