| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | New Jersey Rockets | NCDC | 4 | 0 | 2 | 2 | 0.500 | 0.2788 | 0.3023 | 0.4043 | 0.4384 |
| 2022-23 | Surrey Eagles | BCHL | 48 | 14 | 17 | 31 | 0.646 | 0.2406 | 0.2448 | 0.9410 | 0.9574 |
| 2023-24 | Surrey Eagles | BCHL | 50 | 19 | 21 | 40 | 0.800 | 0.2980 | 0.2895 | 1.1657 | 1.1326 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Yale | D1 | ECAC | — | 31 | 4 | 6 | 10 | 0.323 |
| 2024-25 | Yale | D1 | ECAC | — | 30 | 3 | 11 | 14 | 0.467 |
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.