| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Charlotte Rush | USPHL-Premier | 38 | 2 | 8 | 10 | 0.263 | 0.0297 | 0.0294 | 0.0895 | 0.0886 |
| 2022-23 | Charlotte Rush | USPHL-Premier | 44 | 9 | 21 | 30 | 0.682 | 0.0769 | 0.0723 | 0.2319 | 0.2181 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Nichols | D3 | CNE | GR | 24 | 1 | 10 | 11 | 0.458 |
| 2024-25 | Nichols | D3 | CNE | SR | 16 | 1 | 2 | 3 | 0.188 |
| 2023-24 | Nichols | D3 | CNE | JR | 20 | 0 | 2 | 2 | 0.100 |
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.