| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Brooklyn Aviators | USPHL-Premier | 40 | 2 | 33 | 35 | 0.875 | 0.1178 | 0.1145 | 0.2979 | 0.2896 |
| 2023-24 | Connecticut Jr. Rangers | USPHL-Premier | 41 | 5 | 80 | 85 | 2.073 | 0.2791 | 0.2578 | 0.7057 | 0.6519 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Mary's | D3 | MIAC | SO | 17 | 0 | 3 | 3 | 0.176 |
| 2024-25 | Saint Mary's | D3 | MIAC | FR | 10 | 1 | 2 | 3 | 0.300 |
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.