| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | USHL | NTDP-U18 | 47 | 20 | 26 | 46 | 0.979 | 0.7589 | 0.7589 | 3.6427 | 3.6427 |
| 2021-22 | USHL | NTDP-U18 | 51 | 27 | 48 | 75 | 1.471 | 1.1403 | 1.1156 | 5.4734 | 5.3549 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Minnesota | D1 | BigTen | FR | 39 | 22 | 38 | 60 | 1.538 |
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.