| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Bismarck Bobcats | NAHL | 9 | 1 | 1 | 2 | 0.222 | 0.0880 | 0.0906 | 0.2333 | 0.2401 |
| 2015-16 | — | MJHL | 60 | 15 | 5 | 20 | 0.333 | 0.0906 | 0.0881 | 0.2100 | 0.2043 |
| 2016-17 | Dauphin Kings | MJHL | 59 | 24 | 23 | 47 | 0.797 | 0.2166 | 0.2001 | 0.5020 | 0.4639 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Concordia | D3 | MIAC | SR | 25 | 2 | 8 | 10 | 0.400 |
| 2020-21 | Concordia | D3 | MIAC | JR | 2 | 0 | 2 | 2 | 1.000 |
| 2020-21 | Concordia (MN) | D1 | — | SR | 2 | 0 | 2 | 2 | 1.000 |
| 2019-20 | Concordia | D3 | MIAC | SO | 14 | 1 | 3 | 4 | 0.286 |
| 2019-20 | Concordia (MN) | D1 | — | JR | 14 | 1 | 3 | 4 | 0.286 |
| 2018-19 | Concordia | D3 | MIAC | FR | 19 | 1 | 0 | 1 | 0.053 |
| 2018-19 | Concordia (MN) | D1 | — | SO | 19 | 1 | 0 | 1 | 0.053 |
| 2017-18 | SUNY Plattsburgh | D3 | — | FR | 7 | 1 | 1 | 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.