| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Waterloo Black Hawks | USHL | 61 | 11 | 13 | 24 | 0.393 | 0.2321 | 0.2507 | 1.1815 | 1.2762 |
| 2022-23 | Waterloo Black Hawks | USHL | 57 | 15 | 10 | 25 | 0.439 | 0.2587 | 0.2660 | 1.3173 | 1.3544 |
| 2023-24 | Madison Capitols | USHL | 57 | 17 | 36 | 53 | 0.930 | 0.5485 | 0.5367 | 2.7926 | 2.7326 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Ohio State | D1 | BigTen | SO | 33 | 4 | 9 | 13 | 0.394 |
| 2024-25 | Ohio State | D1 | BigTen | — | 34 | 4 | 9 | 13 | 0.382 |
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.