| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | North Bay Trappers | NOJHL | 41 | 3 | 0 | 3 | 0.073 | 0.0122 | 0.0125 | 0.0305 | 0.0313 |
| 2014-15 | Mattawa Blackhawks | NOJHL | 52 | 4 | 33 | 37 | 0.712 | 0.1188 | 0.1148 | 0.2962 | 0.2863 |
| 2015-16 | Powassan VooDoos | NOJHL | 54 | 12 | 35 | 47 | 0.870 | 0.1454 | 0.1336 | 0.3623 | 0.3328 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Utica | D3 | UCHC | — | 6 | 0 | 1 | 1 | 0.167 |
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.