| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Pembroke Lumber Kings | CCHL | 54 | 18 | 19 | 37 | 0.685 | 0.1956 | 0.1905 | 0.5304 | 0.5165 |
| 2023-24 | Shreveport Mudbugs | NAHL | 50 | 17 | 16 | 33 | 0.660 | 0.2451 | 0.2316 | 0.6988 | 0.6604 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | SUNY Oswego | D3 | SUNYAC | SO | 28 | 15 | 13 | 28 | 1.000 |
| 2024-25 | SUNY Oswego | D3 | SUNYAC | FR | 26 | 5 | 18 | 23 | 0.885 |
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.