| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Rockland Nationals | CCHL | 52 | 11 | 7 | 18 | 0.346 | 0.0988 | 0.1077 | 0.2680 | 0.2922 |
| 2022-23 | Estevan Bruins | SJHL | 30 | 11 | 8 | 19 | 0.633 | 0.1830 | 0.1933 | 0.4767 | 0.5036 |
| 2023-24 | Estevan Bruins | SJHL | 52 | 9 | 14 | 23 | 0.442 | 0.1278 | 0.1289 | 0.3330 | 0.3359 |
| 2024-25 | Drayton Valley Thunder | AJHL | 27 | 9 | 10 | 19 | 0.704 | 0.2350 | 0.2214 | 0.6532 | 0.6153 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | SUNY Plattsburgh | D3 | SUNYAC | FR | 26 | 9 | 6 | 15 | 0.577 |
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.