| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Philadelphia Rebels | NAHL | 10 | 2 | 3 | 5 | 0.500 | 0.1837 | 0.2008 | 0.5278 | 0.5768 |
| 2022-23 | El Paso Rhinos | NAHL | 49 | 9 | 7 | 16 | 0.327 | 0.1200 | 0.1252 | 0.3446 | 0.3597 |
| 2023-24 | El Paso Rhinos | NAHL | 56 | 9 | 18 | 27 | 0.482 | 0.1771 | 0.1764 | 0.5089 | 0.5068 |
| 2024-25 | El Paso Rhinos | NAHL | 59 | 18 | 19 | 37 | 0.627 | 0.2304 | 0.2174 | 0.6619 | 0.6245 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Wisconsin-Superior | D3 | WIAC | FR | 25 | 5 | 6 | 11 | 0.440 |
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.