| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Sioux City Musketeers | USHL | 50 | 1 | 5 | 6 | 0.120 | 0.0708 | 0.0781 | 0.3604 | 0.3977 |
| 2023-24 | Salmon Arm Silverbacks | BCHL | 50 | 5 | 8 | 13 | 0.260 | 0.1002 | 0.1082 | — | — |
| 2024-25 | Green Bay Gamblers | USHL | 62 | 1 | 10 | 11 | 0.177 | 0.1046 | 0.1049 | 0.5328 | 0.5343 |
| 2025-26 | Salmon Arm Silverbacks | BCHL | 47 | 5 | 15 | 20 | 0.425 | 0.1639 | 0.1627 | 0.6192 | 0.6147 |
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.