| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Brynäs IF | SDHL | 26 | 1 | 2 | 3 | 0.115 | 0.1333 | 0.1333 | — | — |
| 2022-23 | Brynäs IF | SDHL | 26 | 1 | 3 | 4 | 0.154 | 0.1776 | 0.1776 | — | — |
| 2023-24 | Brynäs IF | SDHL | 10 | 1 | 1 | 2 | 0.200 | 0.2310 | 0.2310 | — | — |
| 2024-25 | Brynäs IF | SDHL | 33 | 0 | 3 | 3 | 0.091 | 0.1050 | 0.1050 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Mercyhurst | D1 | CHA-W | — | 37 | 4 | 15 | 19 | 0.513 |
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.