| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | NAHL | 26 | 5 | 2 | 7 | 0.269 | 0.0989 | 0.1089 | — | — |
| 2015-16 | Austin Bruins | NAHL | 52 | 19 | 12 | 31 | 0.596 | 0.2190 | 0.2315 | 0.6293 | 0.6652 |
| 2016-17 | Dubuque Fighting Saints | USHL | 57 | 17 | 10 | 27 | 0.474 | 0.2794 | 0.2715 | 1.4227 | 1.3826 |
| 2024-25 | Kärpät | Liiga | 60 | 17 | 13 | 30 | 0.500 | 1.2500 | 1.2130 | 4.2980 | 4.1708 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Western Michigan | D1 | NCHC | JR | 36 | 12 | 14 | 26 | 0.722 |
| 2018-19 | Western Michigan | D1 | NCHC | SO | 36 | 13 | 14 | 27 | 0.750 |
| 2017-18 | Western Michigan | D1 | NCHC | FR | 33 | 10 | 7 | 17 | 0.515 |
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.