| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | El Paso Rhinos | NAHL | 8 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | — | NAHL | 38 | 0 | 2 | 2 | 0.053 | 0.0208 | 0.0215 | 0.0552 | 0.0571 |
| 2023-24 | New Mexico Ice Wolves | NAHL | 55 | 0 | 9 | 9 | 0.164 | 0.0648 | 0.0640 | 0.1718 | 0.1696 |
| 2024-25 | New Mexico Ice Wolves | NAHL | 56 | 5 | 12 | 17 | 0.304 | 0.1203 | 0.1125 | 0.3187 | 0.2979 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan Tech | D1 | CCHA | FR | 1 | 0 | 0 | 0 | 0.000 |
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.