| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Pembroke Lumber Kings | CCHL | 14 | 0 | 1 | 1 | 0.071 | 0.0155 | 0.0175 | 0.0552 | 0.0624 |
| 2022-23 | Johnstown Tomahawks | NAHL | 45 | 0 | 8 | 8 | 0.178 | 0.0653 | 0.0721 | 0.1877 | 0.2072 |
| 2023-24 | Johnstown Tomahawks | NAHL | 51 | 4 | 6 | 10 | 0.196 | 0.0720 | 0.0760 | 0.2070 | 0.2186 |
| 2024-25 | — | BCHL | 47 | 1 | 3 | 4 | 0.085 | 0.0328 | 0.0324 | 0.1238 | 0.1221 |
| 2025-26 | Prince George Spruce Kings | BCHL | 42 | 2 | 7 | 9 | 0.214 | 0.0826 | 0.0784 | 0.3119 | 0.2962 |
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.