| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Georgetown Raiders | OJHL | 54 | 5 | 11 | 16 | 0.296 | 0.0890 | 0.0953 | 0.2028 | 0.2171 |
| 2022-23 | Georgetown Raiders | OJHL | 53 | 12 | 20 | 32 | 0.604 | 0.1814 | 0.1849 | 0.4133 | 0.4214 |
| 2023-24 | — | OJHL | 51 | 22 | 35 | 57 | 1.118 | 0.3357 | 0.3248 | 0.7650 | 0.7402 |
| 2024-25 | — | OJHL | 55 | 15 | 36 | 51 | 0.927 | 0.2786 | 0.2553 | 0.6347 | 0.5815 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Buffalo State | D3 | SUNYAC | FR | 25 | 10 | 8 | 18 | 0.720 |
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.