| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Kent School | NE-Prep | 26 | 0 | 3 | 3 | 0.115 | 0.0232 | 0.0232 | 0.0528 | 0.0528 |
| 2022-23 | Kent School | NE-Prep | 25 | 2 | 6 | 8 | 0.320 | 0.0644 | 0.0644 | 0.1463 | 0.1463 |
| 2023-24 | Kent School | NE-Prep | 28 | 3 | 7 | 10 | 0.357 | 0.0718 | 0.0718 | 0.1633 | 0.1633 |
| 2024-25 | Lone Star Brahmas | NAHL | 23 | 0 | 4 | 4 | 0.174 | 0.0639 | 0.0630 | 0.1838 | 0.1812 |
| 2025-26 | Lone Star Brahmas | NAHL | 58 | 10 | 23 | 33 | 0.569 | 0.2091 | 0.1958 | 0.6014 | 0.5633 |
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.