| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | New Jersey Jr. Titans | EHL | 28 | 9 | 9 | 18 | 0.643 | 0.1380 | 0.1468 | 0.3148 | 0.3349 |
| 2015-16 | Kenai River Brown Bears | NAHL | 7 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2016-17 | Philadelphia Revolution | EHL | 47 | 33 | 41 | 74 | 1.575 | 0.3379 | 0.3293 | 0.7710 | 0.7515 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | SUNY Plattsburgh | D3 | — | JR | 15 | 3 | 4 | 7 | 0.467 |
| 2018-19 | SUNY Plattsburgh | D3 | — | SO | 25 | 7 | 4 | 11 | 0.440 |
| 2017-18 | SUNY Plattsburgh | D3 | — | FR | 26 | 17 | 7 | 24 | 0.923 |
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.