| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | NOJHL | 23 | 5 | 11 | 16 | 0.696 | 0.0991 | 0.0951 | 0.2886 | 0.2769 |
| 2022-23 | Charlotte Rush | USPHL-Premier | 39 | 17 | 34 | 51 | 1.308 | 0.1475 | 0.1372 | 0.4449 | 0.4139 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Suffolk | D3 | CNE | GR | 26 | 4 | 11 | 15 | 0.577 |
| 2024-25 | Suffolk | D3 | CNE | SR | 20 | 4 | 2 | 6 | 0.300 |
| 2023-24 | Suffolk | D3 | CNE | JR | 15 | 2 | 4 | 6 | 0.400 |
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.