| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Johnstown Tomahawks | NAHL | 35 | 12 | 12 | 24 | 0.686 | 0.2519 | 0.2581 | 0.7238 | 0.7415 |
| 2023-24 | Johnstown Tomahawks | NAHL | 54 | 20 | 33 | 53 | 0.982 | 0.3606 | 0.3522 | 1.0360 | 1.0118 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Stonehill | D1 | AHA | — | 30 | 4 | 7 | 11 | 0.367 |
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.