| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | — | NAHL | 62 | 4 | 12 | 16 | 0.258 | 0.0948 | 0.1002 | 0.2724 | 0.2880 |
| 2014-15 | Omaha Lancers | USHL | 57 | 1 | 7 | 8 | 0.140 | 0.0828 | 0.0805 | 0.4217 | 0.4102 |
| 2015-16 | Omaha Lancers | USHL | 51 | 2 | 10 | 12 | 0.235 | 0.1388 | 0.1286 | 0.7067 | 0.6547 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Minnesota | D1 | BigTen | — | 0 | 0 | 0 | 0 | 0.000 |
| 2017-18 | Minnesota | D1 | BigTen | — | 0 | 0 | 0 | 0 | 0.000 |
| 2016-17 | Minnesota State | D1 | WCHA | FR | 7 | 0 | 2 | 2 | 0.286 |
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.