| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Charlotte Rush | USPHL-Premier | 32 | 17 | 28 | 45 | 1.406 | 0.1586 | 0.1586 | 0.4784 | 0.4784 |
| 2021-22 | — | NAHL | 54 | 8 | 15 | 23 | 0.426 | 0.1513 | 0.1492 | 0.4472 | 0.4409 |
| 2022-23 | Amarillo Wranglers | NAHL | 34 | 2 | 5 | 7 | 0.206 | 0.0731 | 0.0685 | 0.2162 | 0.2025 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Nichols | D3 | CNE | GR | 27 | 9 | 11 | 20 | 0.741 |
| 2024-25 | Nichols | D3 | CNE | SR | 25 | 6 | 5 | 11 | 0.440 |
| 2023-24 | Nichols | D3 | CNE | JR | 15 | 4 | 0 | 4 | 0.267 |
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.