| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Minnesota Moose | NA3HL | 10 | 6 | 5 | 11 | 1.100 | 0.1326 | 0.1465 | 0.3475 | 0.3838 |
| 2023-24 | Minnesota Moose | NA3HL | 44 | 20 | 33 | 53 | 1.204 | 0.1451 | 0.1467 | 0.3805 | 0.3847 |
| 2024-25 | Rochester Grizzlies | NA3HL | 29 | 18 | 18 | 36 | 1.241 | 0.1496 | 0.1435 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Mary's | D3 | MIAC | FR | 2 | 1 | 0 | 1 | 0.500 |
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.