| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | U.S. National U17 Team | NTDP-U18 | 60 | 1 | 10 | 11 | 0.183 | 0.1362 | 0.1403 | 0.6840 | 0.7045 |
| 2023-24 | U.S. National U18 Team | NTDP-U18 | 53 | 1 | 8 | 9 | 0.170 | 0.1262 | 0.1235 | 0.6336 | 0.6201 |
| 2024-25 | Chicago Steel | USHL | 58 | 1 | 10 | 11 | 0.190 | 0.1119 | 0.1124 | 0.5697 | 0.5721 |
| 2025-26 | Tri-City Storm | USHL | 45 | 6 | 3 | 9 | 0.200 | 0.1180 | 0.1128 | 0.6007 | 0.5742 |
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.