| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Vernon Vipers | BCHL | 53 | 9 | 15 | 24 | 0.453 | 0.1687 | 0.1758 | 0.6598 | 0.6877 |
| 2023-24 | Vernon Vipers | BCHL | 51 | 23 | 16 | 39 | 0.765 | 0.2849 | 0.2839 | 1.1142 | 1.1103 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Lawrence | D1 | ECAC | SO | 33 | 8 | 8 | 16 | 0.485 |
| 2024-25 | St. Lawrence | D1 | ECAC | — | 33 | 4 | 8 | 12 | 0.364 |
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.