| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | New Jersey Rockets | NCDC | 29 | 3 | 2 | 5 | 0.172 | 0.0486 | 0.0477 | 0.1396 | 0.1371 |
| 2018-19 | New Jersey Rockets | USPHL-Premier | 27 | 16 | 12 | 28 | 1.037 | 0.1396 | 0.1282 | 0.3530 | 0.3243 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | King's | D3 | MAC | — | 10 | 4 | 4 | 8 | 0.800 |
| 2019-20 | Bryn Athyn | D3 | — | FR | 13 | 2 | 1 | 3 | 0.231 |
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.