| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | — | USHL | 49 | 18 | 18 | 36 | 0.735 | 0.4516 | 0.4516 | 2.1646 | 2.1646 |
| 2021-22 | — | USHL | 54 | 37 | 37 | 74 | 1.370 | 0.8424 | 0.9052 | 4.0375 | 4.3386 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Michigan | D1 | BigTen | — | 36 | 30 | 35 | 65 | 1.806 |
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.