| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | MoDo Hockey U20 | SHL-J20 | 14 | 0 | 1 | 1 | 0.071 | 0.0397 | 0.0434 | 0.0951 | 0.1041 |
| 2023-24 | MoDo Hockey U20 | SuperElit | 42 | 0 | 12 | 12 | 0.286 | 0.1127 | 0.1178 | 0.3880 | 0.4056 |
| 2024-25 | MoDo Hockey U20 | SuperElit | 32 | 3 | 10 | 13 | 0.406 | 0.1603 | 0.1595 | 0.5517 | 0.5490 |
| 2025-26 | Rögle BK U20 | SHL-J20 | 36 | 4 | 20 | 24 | 0.667 | 0.3706 | 0.3540 | 0.8883 | 0.8485 |
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.