| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Smiths Falls Bears | CCHL | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | Kirkland Lake Gold Miners | NOJHL | 32 | 1 | 8 | 9 | 0.281 | 0.0715 | 0.0701 | 0.1167 | 0.1144 |
| 2022-23 | Kirkland Lake Gold Miners | NOJHL | 57 | 0 | 12 | 12 | 0.210 | 0.0535 | 0.0501 | 0.0873 | 0.0818 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | SUNY Potsdam | D3 | SUNYAC | JR | 17 | 0 | 2 | 2 | 0.118 |
| 2024-25 | SUNY Potsdam | D3 | SUNYAC | SO | 8 | 0 | 0 | 0 | 0.000 |
| 2023-24 | SUNY Potsdam | D3 | SUNYAC | FR | 21 | 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.