| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | New Jersey Rockets | EHL | 12 | 5 | 8 | 13 | 1.083 | 0.2325 | 0.2388 | 0.5305 | 0.5448 |
| 2015-16 | New Jersey Rockets | EHL | 35 | 28 | 26 | 54 | 1.543 | 0.3311 | 0.3255 | 0.7556 | 0.7427 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | SUNY Cortland | D3 | — | SR | 22 | 9 | 9 | 18 | 0.818 |
| 2018-19 | SUNY Cortland | D3 | — | JR | 22 | 1 | 7 | 8 | 0.364 |
| 2017-18 | SUNY Cortland | D3 | — | SO | 21 | 5 | 5 | 10 | 0.476 |
| 2016-17 | SUNY Cortland | D3 | — | FR | 25 | 5 | 14 | 19 | 0.760 |
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.