| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Madison Capitols | USHL | 50 | 25 | 16 | 41 | 0.820 | 0.5222 | 0.5222 | 2.4573 | 2.4573 |
| 2020-21 | Green Bay Gamblers | USHL | 50 | 21 | 16 | 37 | 0.740 | 0.4712 | 0.4712 | 2.2176 | 2.2176 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Arizona State | D1 | NCHC | — | 37 | 26 | 13 | 39 | 1.054 |
| 2023-24 | Penn State | D1 | BigTen | JR | 36 | 13 | 13 | 26 | 0.722 |
| 2022-23 | Penn State | D1 | BigTen | SO | 28 | 8 | 9 | 17 | 0.607 |
| 2021-22 | Penn State | D1 | BigTen | FR | 36 | 13 | 13 | 26 | 0.722 |
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.