| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Philadelphia Little Flyers | EHL | 47 | 14 | 32 | 46 | 0.979 | 0.2261 | 0.2310 | 0.4789 | 0.4893 |
| 2017-18 | Philadelphia Little Flyers | EHL | 49 | 31 | 65 | 96 | 1.959 | 0.4526 | 0.4373 | 0.9586 | 0.9262 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Utica | D1 | UCHC | FR | 11 | 3 | 4 | 7 | 0.636 |
| 2018-19 | Utica | D3 | UCHC | — | 11 | 3 | 4 | 7 | 0.636 |
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.