| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Langley Rivermen | BCHL | 46 | 1 | 4 | 5 | 0.109 | 0.0405 | 0.0428 | 0.1584 | 0.1674 |
| 2023-24 | New Jersey Jr. Titans | NAHL | 43 | 2 | 11 | 13 | 0.302 | 0.1198 | 0.1234 | 0.3174 | 0.3270 |
| 2024-25 | New Jersey Jr. Titans | NAHL | 50 | 3 | 30 | 33 | 0.660 | 0.2615 | 0.2557 | 0.6929 | 0.6775 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Boston University | D1 | HockeyEast | FR | 3 | 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.