| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Long Beach Sharks | NA3HL | 42 | 13 | 23 | 36 | 0.857 | 0.1033 | 0.1024 | 0.2708 | 0.2685 |
| 2017-18 | Brooklyn Aviators | USPHL-Premier | 44 | 33 | 51 | 84 | 1.909 | 0.2570 | 0.2434 | 0.6499 | 0.6154 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Northland | D3 | — | JR | 4 | 1 | 0 | 1 | 0.250 |
| 2019-20 | Northland | D3 | — | SO | 12 | 0 | 1 | 1 | 0.083 |
| 2018-19 | Northland | D3 | — | FR | 5 | 0 | 1 | 1 | 0.200 |
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.