| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | NA3HL | 38 | 5 | 13 | 18 | 0.474 | 0.0594 | 0.0605 | 0.1495 | 0.1522 |
| 2015-16 | Coulee Region Chill | NA3HL | 43 | 21 | 18 | 39 | 0.907 | 0.1138 | 0.1103 | 0.2863 | 0.2774 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Augsburg | D1 | MIAC | SO | 26 | 1 | 7 | 8 | 0.308 |
| 2019-20 | Augsburg | D3 | MIAC | — | 26 | 1 | 7 | 8 | 0.308 |
| 2018-19 | Augsburg | D1 | MIAC | FR | 14 | 1 | 0 | 1 | 0.071 |
| 2018-19 | Augsburg | D3 | MIAC | — | 14 | 1 | 0 | 1 | 0.071 |
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.