| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | U.S. National U17 Team | NTDP-U18 | 4 | 1 | 1 | 2 | 0.500 | 0.3877 | 0.3948 | 1.8610 | 1.8949 |
| 2022-23 | New Jersey Jr. Titans | NAHL | 50 | 7 | 17 | 24 | 0.480 | 0.1902 | 0.2062 | — | — |
| 2023-24 | Chicago Steel | USHL | 62 | 10 | 21 | 31 | 0.500 | 0.3074 | 0.3045 | 1.4731 | 1.4594 |
| 2024-25 | Chicago Steel | USHL | 51 | 13 | 26 | 39 | 0.765 | 0.4701 | 0.4417 | 2.2530 | 2.1171 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Merrimack | D1 | HockeyEast | — | 13 | 2 | 0 | 2 | 0.154 |
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.