| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Maine Nordiques | NAHL | 4 | 1 | 1 | 2 | 0.500 | 0.1981 | 0.2153 | 0.5250 | 0.5707 |
| 2022-23 | Maine Nordiques | NAHL | 58 | 20 | 20 | 40 | 0.690 | 0.2733 | 0.2837 | 0.7241 | 0.7515 |
| 2023-24 | Victoria Grizzlies | BCHL | 49 | 9 | 7 | 16 | 0.327 | 0.1216 | 0.1180 | 0.4757 | 0.4617 |
| 2024-25 | New Hampshire Mountain Kings | NAHL | 59 | 41 | 36 | 77 | 1.305 | 0.5171 | 0.4848 | 1.3702 | 1.2847 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Air Force | D1 | AHA | — | 24 | 5 | 2 | 7 | 0.292 |
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.