| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Chaska | USHS-MN | 25 | 5 | 17 | 22 | 0.880 | 0.1114 | 0.1114 | 0.2138 | 0.2138 |
| 2020-21 | New Ulm Steel | NA3HL | 29 | 2 | 13 | 15 | 0.517 | 0.0649 | 0.0649 | 0.1633 | 0.1633 |
| 2021-22 | Aberdeen Wings | NAHL | 32 | 0 | 5 | 5 | 0.156 | 0.0574 | 0.0556 | 0.1649 | 0.1597 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Concordia | D3 | MIAC | — | 23 | 0 | 14 | 14 | 0.609 |
| 2022-23 | Concordia | D3 | MIAC | — | 26 | 1 | 7 | 8 | 0.308 |
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.