| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Sartell | USHS-MN | 25 | 10 | 9 | 19 | 0.760 | 0.0962 | 0.0962 | 0.1846 | 0.1846 |
| 2022-23 | Sartell | USHS-MN | 27 | 20 | 22 | 42 | 1.556 | 0.1969 | 0.1969 | 0.3779 | 0.3779 |
| 2023-24 | Sartell | USHS-MN | 26 | 16 | 11 | 27 | 1.038 | 0.1315 | 0.1315 | 0.2523 | 0.2523 |
| 2024-25 | Rochester Grizzlies | NA3HL | 36 | 4 | 4 | 8 | 0.222 | 0.0279 | 0.0279 | 0.0701 | 0.0701 |
| 2025-26 | — | NA3HL | 47 | 25 | 21 | 46 | 0.979 | 0.1228 | 0.1166 | 0.3090 | 0.2933 |
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.