| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | — | NAHL | 34 | 5 | 2 | 7 | 0.206 | 0.0731 | 0.0747 | 0.2162 | 0.2209 |
| 2015-16 | Johnstown Tomahawks | NAHL | 48 | 11 | 16 | 27 | 0.562 | 0.1998 | 0.1953 | 0.5906 | 0.5773 |
| 2016-17 | Johnstown Tomahawks | NAHL | 39 | 9 | 16 | 25 | 0.641 | 0.2277 | 0.2102 | 0.6730 | 0.6213 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | SUNY Oswego | D3 | — | SO | 7 | 0 | 0 | 0 | 0.000 |
| 2017-18 | SUNY Oswego | D3 | — | FR | 10 | 1 | 3 | 4 | 0.400 |
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.