| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | USHS-MN | 25 | 6 | 5 | 11 | 0.440 | 0.0557 | 0.0591 | 0.1069 | 0.1134 |
| 2015-16 | — | USHL | 57 | 1 | 15 | 16 | 0.281 | 0.1656 | 0.1835 | 0.8431 | 0.9343 |
| 2016-17 | — | USHL | 54 | 5 | 29 | 34 | 0.630 | 0.3714 | 0.3926 | 1.8909 | 1.9989 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Minnesota Duluth | D1 | NCHC | SO | 40 | 6 | 21 | 27 | 0.675 |
| 2017-18 | Minnesota Duluth | D1 | NCHC | FR | 39 | 5 | 18 | 23 | 0.590 |
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.