| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Cushing Academy | NE-Prep | 27 | 2 | 0 | 2 | 0.074 | 0.0147 | 0.0147 | 0.0338 | 0.0338 |
| 2022-23 | Cushing Academy | NE-Prep | 32 | 2 | 4 | 6 | 0.188 | 0.0371 | 0.0371 | 0.0854 | 0.0854 |
| 2023-24 | Cushing Academy | NE-Prep | 32 | 7 | 7 | 14 | 0.438 | 0.0867 | 0.0867 | 0.1993 | 0.1993 |
| 2024-25 | Cushing Academy | NE-Prep | 23 | 8 | 13 | 21 | 0.913 | 0.1809 | 0.1809 | 0.4160 | 0.4160 |
| 2025-26 | Cushing Academy | NE-Prep | 33 | 8 | 24 | 32 | 0.970 | 0.1921 | 0.1921 | 0.4418 | 0.4418 |
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.