| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | U.S. National U17 Team | NTDP-U18 | 54 | 5 | 30 | 35 | 0.648 | 0.5025 | 0.5204 | 2.4122 | 2.4981 |
| 2024-25 | U.S. National U18 Team | NTDP-U18 | 66 | 5 | 27 | 32 | 0.485 | 0.3759 | 0.3716 | 1.8044 | 1.7838 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Harvard | D1 | ECAC | FR | 28 | 1 | 1 | 2 | 0.071 |
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.