| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Amarillo Wranglers | NAHL | 3 | 0 | 1 | 1 | 0.333 | 0.1184 | 0.1251 | 0.3499 | 0.3696 |
| 2023-24 | — | NAHL | 47 | 2 | 2 | 4 | 0.085 | 0.0302 | 0.0305 | 0.0893 | 0.0901 |
| 2024-25 | Springfield Jr. Blues | NAHL | 54 | 2 | 7 | 9 | 0.167 | 0.0592 | 0.0566 | 0.1750 | 0.1673 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Buffalo State | D3 | SUNYAC | FR | 23 | 0 | 2 | 2 | 0.087 |
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.