| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Breck | USHS-MN | 22 | 2 | 4 | 6 | 0.273 | 0.0734 | 0.0734 | 0.0662 | 0.0662 |
| 2023-24 | Breck | USHS-MN | 26 | 18 | 28 | 46 | 1.769 | 0.4763 | 0.4763 | 0.4297 | 0.4297 |
| 2024-25 | Breck | USHS-MN | 25 | 24 | 27 | 51 | 2.040 | 0.5492 | 0.5492 | 0.4955 | 0.4955 |
| 2025-26 | Breck | USHS-MN | 26 | 32 | 46 | 78 | 3.000 | 0.8076 | 0.8076 | — | — |
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.