| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Dexter | NE-Prep | 25 | 2 | 11 | 13 | 0.520 | 0.1467 | 0.1467 | 0.2380 | 0.2380 |
| 2022-23 | Dexter | NE-Prep | 31 | 2 | 1 | 3 | 0.097 | 0.0273 | 0.0273 | 0.0443 | 0.0443 |
| 2023-24 | Tri-City Storm | USHL | 16 | 0 | 1 | 1 | 0.062 | 0.0384 | 0.0375 | 0.1841 | 0.1797 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Harvard | D1 | ECAC | SO | 34 | 2 | 1 | 3 | 0.088 |
| 2024-25 | Harvard | D1 | ECAC | — | 11 | 0 | 2 | 2 | 0.182 |
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.