| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Gentry Academy | USHS-MN | 25 | 1 | 1 | 2 | 0.080 | 0.0101 | 0.0101 | 0.0194 | 0.0194 |
| 2022-23 | Gentry Academy | USHS-MN | 27 | 19 | 12 | 31 | 1.148 | 0.1453 | 0.1453 | 0.2788 | 0.2788 |
| 2023-24 | Chicago Steel | USHL | 5 | 1 | 2 | 3 | 0.600 | 0.3539 | 0.3879 | 1.8004 | 1.9734 |
| 2024-25 | Chicago Steel | USHL | 29 | 1 | 2 | 3 | 0.103 | 0.0610 | 0.0637 | 0.3103 | 0.3243 |
| 2025-26 | Sioux Falls Stampede | USHL | 61 | 15 | 27 | 42 | 0.689 | 0.4061 | 0.4048 | 2.0660 | 2.0594 |
| 2026-27 | Sioux Falls Stampede | USHL | 6 | 4 | 3 | 7 | 1.167 | 0.6882 | 0.6882 | 3.5009 | 3.5009 |
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.