| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | New Jersey Rockets | NCDC | 48 | 8 | 24 | 32 | 0.667 | 0.3718 | 0.4046 | 0.5391 | 0.5866 |
| 2022-23 | Coquitlam Express | BCHL | 52 | 4 | 28 | 32 | 0.615 | 0.2292 | 0.2340 | 0.8967 | 0.9157 |
| 2023-24 | Green Bay Gamblers | USHL | 62 | 3 | 6 | 9 | 0.145 | 0.0893 | 0.0848 | 0.4278 | 0.4061 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Canisius | D1 | AHA | SO | 35 | 1 | 9 | 10 | 0.286 |
| 2024-25 | Penn State | D1 | BigTen | — | 12 | 0 | 0 | 0 | 0.000 |
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.