| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | New Jersey Rockets | NCDC | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Austin Bruins | NAHL | 59 | 5 | 15 | 20 | 0.339 | 0.1343 | 0.1489 | 0.3559 | 0.3945 |
| 2023-24 | Dubuque Fighting Saints | USHL | 46 | 3 | 11 | 14 | 0.304 | 0.1871 | 0.1899 | 0.8965 | 0.9100 |
| 2024-25 | Dubuque Fighting Saints | USHL | 62 | 14 | 24 | 38 | 0.613 | 0.3767 | 0.3631 | 1.8057 | 1.7407 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Brown | D1 | ECAC | FR | 31 | 4 | 8 | 12 | 0.387 |
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.