| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Green Bay Gamblers | USHL | 50 | 11 | 4 | 15 | 0.300 | 0.1770 | 0.1973 | 0.9010 | 1.0043 |
| 2014-15 | Green Bay Gamblers | USHL | 33 | 10 | 17 | 27 | 0.818 | 0.4827 | 0.5143 | 2.4574 | 2.6184 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Minnesota | D1 | BigTen | — | 38 | 13 | 18 | 31 | 0.816 |
| 2017-18 | Minnesota | D1 | BigTen | — | 38 | 12 | 14 | 26 | 0.684 |
| 2016-17 | Minnesota | D1 | BigTen | — | 37 | 14 | 7 | 21 | 0.568 |
| 2015-16 | Minnesota | D1 | BigTen | — | 35 | 3 | 4 | 7 | 0.200 |
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.