| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Tampa Bay Juniors | USPHL-Elite | 42 | 29 | 27 | 56 | 1.333 | 0.1231 | 0.1245 | 0.3053 | 0.3087 |
| 2017-18 | Maine Wild | NA3HL | 46 | 33 | 27 | 60 | 1.304 | 0.1637 | 0.1568 | 0.4118 | 0.3944 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Framingham State | D1 | MASCAC | FR | 10 | 1 | 2 | 3 | 0.300 |
| 2018-19 | Framingham State | D3 | MASCAC | — | 10 | 1 | 2 | 3 | 0.300 |
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.