| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Springfield Jr. Pics | USPHL-Elite | 34 | 8 | 12 | 20 | 0.588 | 0.1033 | 0.1093 | 0.1348 | 0.1427 |
| 2022-23 | Springfield Jr. Pics | USPHL-Premier | 33 | 2 | 6 | 8 | 0.242 | 0.0799 | 0.0842 | 0.0825 | 0.0869 |
| 2023-24 | Kirkland Lake Gold Miners | NOJHL | 52 | 2 | 2 | 4 | 0.077 | 0.0196 | 0.0194 | 0.0319 | 0.0315 |
| 2024-25 | Kirkland Lake Gold Miners | NOJHL | 10 | 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.