| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Houston Bulls | NAHL | 21 | 0 | 1 | 1 | 0.048 | 0.0189 | 0.0188 | 0.0500 | 0.0496 |
| 2022-23 | Islanders Hockey Club | NCDC | 50 | 5 | 8 | 13 | 0.260 | 0.1450 | 0.1373 | 0.2102 | 0.1991 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | SUNY Cortland | D3 | SUNYAC | SO | 12 | 0 | 1 | 1 | 0.083 |
| 2023-24 | SUNY Cortland | D3 | SUNYAC | FR | 12 | 0 | 2 | 2 | 0.167 |
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.