| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | — | USPHL-Premier | 23 | 16 | 15 | 31 | 1.348 | 0.1520 | 0.1520 | 0.4585 | 0.4585 |
| 2021-22 | Avto Yekaterinburg | MHL-RU | 49 | 13 | 13 | 26 | 0.531 | 0.2610 | 0.2475 | 1.1918 | 1.1303 |
| 2022-23 | Utica Jr. Comets | NCDC | 49 | 20 | 22 | 42 | 0.857 | 0.1981 | 0.1873 | 0.6931 | 0.6554 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | SUNY Plattsburgh | D3 | SUNYAC | JR | 24 | 5 | 7 | 12 | 0.500 |
| 2023-24 | Utica | D3 | UCHC | — | 25 | 4 | 7 | 11 | 0.440 |
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.