| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Neepawa Titans | MJHL | 42 | 9 | 2 | 11 | 0.262 | 0.0741 | 0.0722 | 0.1650 | 0.1607 |
| 2014-15 | Neepawa Titans | MJHL | 58 | 22 | 16 | 38 | 0.655 | 0.1854 | 0.1710 | 0.4128 | 0.3806 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | St. Norbert | D3 | NCHA | SR | 31 | 7 | 11 | 18 | 0.581 |
| 2017-18 | St. Norbert | D3 | NCHA | JR | 32 | 9 | 12 | 21 | 0.656 |
| 2016-17 | St. Norbert | D3 | NCHA | SO | 29 | 9 | 10 | 19 | 0.655 |
| 2015-16 | St. Norbert | D3 | NCHA | FR | 31 | 7 | 5 | 12 | 0.387 |
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.