| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Moorhead | USHS-MN | 30 | 7 | 31 | 38 | 1.267 | 0.1604 | 0.1604 | 0.3076 | 0.3076 |
| 2023-24 | Moorhead | USHS-MN | 27 | 15 | 25 | 40 | 1.482 | 0.1876 | 0.1876 | 0.3597 | 0.3597 |
| 2024-25 | Cedar Rapids RoughRiders | USHL | 8 | 1 | 0 | 1 | 0.125 | 0.0737 | 0.0765 | 0.3751 | 0.3893 |
| 2025-26 | Wenatchee Wild | WHL | 54 | 14 | 26 | 40 | 0.741 | 0.3604 | 0.3557 | 1.8093 | 1.7857 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | Minnesota State | D1 | CCHA | FR | 0 | 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.