| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Andover | USHS-MN | 22 | 1 | 4 | 5 | 0.227 | 0.0280 | 0.0280 | 0.0552 | 0.0552 |
| 2023-24 | Wisconsin Woodsmen | NA3HL | 43 | 5 | 21 | 26 | 0.605 | 0.0669 | 0.0696 | — | — |
| 2024-25 | Wisconsin Woodsmen | NA3HL | 45 | 16 | 28 | 44 | 0.978 | 0.1081 | 0.1068 | 0.3098 | 0.3062 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Hamline | D3 | MIAC | — | 25 | 4 | 12 | 16 | 0.640 |
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.