| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Texas Jr. Brahmas | NA3HL | 43 | 4 | 12 | 16 | 0.372 | 0.0412 | 0.0412 | 0.1175 | 0.1175 |
| 2023-24 | Vermont Lumberjacks | EHL | 44 | 6 | 7 | 13 | 0.295 | 0.0433 | 0.0424 | 0.1447 | 0.1418 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Misericordia | D3 | MAC | SO | 14 | 0 | 1 | 1 | 0.071 |
| 2024-25 | Misericordia | D3 | MAC | — | 12 | 0 | 0 | 0 | 0.000 |
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.