| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Malmö Redhawks U20 | SHL-J20 | 12 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | Malmö Redhawks U20 | SuperElit | 10 | 0 | 1 | 1 | 0.100 | 0.0395 | 0.0417 | 0.1358 | 0.1433 |
| 2024-25 | Malmö Redhawks U20 | SuperElit | 46 | 9 | 14 | 23 | 0.500 | 0.1973 | 0.1982 | 0.6791 | 0.6823 |
| 2025-26 | Muskegon Lumberjacks | USHL | 24 | 1 | 10 | 11 | 0.458 | 0.2704 | 0.2596 | 1.3765 | 1.3218 |
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.