| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | — | USHL | 12 | 1 | 5 | 6 | 0.500 | 0.3184 | 0.3373 | 1.4984 | 1.5875 |
| 2013-14 | — | USHL | 54 | 2 | 21 | 23 | 0.426 | 0.2712 | 0.2746 | 1.2763 | 1.2924 |
| 2014-15 | — | USHL | 53 | 7 | 41 | 48 | 0.906 | 0.5767 | 0.5557 | 2.7141 | 2.6151 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Minnesota Duluth | D1 | NCHC | SO | 42 | 7 | 27 | 34 | 0.809 |
| 2015-16 | Minnesota Duluth | D1 | NCHC | FR | 40 | 4 | 13 | 17 | 0.425 |
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.