| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Waterloo Black Hawks | USHL | 47 | 7 | 9 | 16 | 0.340 | 0.2092 | 0.2191 | 1.0029 | 1.0504 |
| 2015-16 | Muskegon Lumberjacks | USHL | 56 | 46 | 43 | 89 | 1.589 | 0.9769 | 0.9778 | 4.6824 | 4.6869 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Minnesota | D1 | BigTen | JR | 38 | 21 | 24 | 45 | 1.184 |
| 2017-18 | Minnesota | D1 | BigTen | SO | 38 | 12 | 19 | 31 | 0.816 |
| 2016-17 | Minnesota | D1 | BigTen | FR | 36 | 14 | 18 | 32 | 0.889 |
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.