| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Charlotte Rush | USPHL-Premier | 28 | 5 | 11 | 16 | 0.571 | 0.0645 | 0.0650 | 0.1944 | 0.1959 |
| 2022-23 | Maryland Black Bears | NAHL | 22 | 1 | 3 | 4 | 0.182 | 0.0646 | 0.0626 | 0.1909 | 0.1851 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Elmira | D3 | UCHC | GR | 21 | 2 | 3 | 5 | 0.238 |
| 2024-25 | Elmira | D3 | UCHC | SR | 4 | 0 | 0 | 0 | 0.000 |
| 2023-24 | Elmira | D3 | UCHC | JR | 14 | 0 | 2 | 2 | 0.143 |
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.