| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Dauphin Kings | MJHL | 56 | 4 | 23 | 27 | 0.482 | 0.0928 | 0.0898 | 0.3040 | 0.2942 |
| 2016-17 | Virden Oil Capitals | MJHL | 56 | 2 | 22 | 24 | 0.429 | 0.0825 | 0.0758 | 0.2703 | 0.2484 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Saint Mary's (MN) | D1 | MIAC | SR | 9 | 0 | 2 | 2 | 0.222 |
| 2020-21 | Saint Mary's (MN) | D3 | MIAC | SR | 9 | 0 | 2 | 2 | 0.222 |
| 2019-20 | Saint Mary's (MN) | D1 | MIAC | JR | 24 | 2 | 2 | 4 | 0.167 |
| 2019-20 | Saint Mary's (MN) | D3 | MIAC | JR | 24 | 2 | 2 | 4 | 0.167 |
| 2018-19 | Wisconsin-Superior | D1 | BigTen | SO | 9 | 0 | 0 | 0 | 0.000 |
| 2018-19 | Wisconsin-Superior | D3 | BigTen | SO | 9 | 0 | 0 | 0 | 0.000 |
| 2017-18 | SUNY Plattsburgh | D3 | SUNYAC | FR | 14 | 1 | 1 | 2 | 0.143 |
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.