| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Västerås IK U20 | SuperElit | 10 | 0 | 1 | 1 | 0.100 | 0.0395 | 0.0395 | 0.1378 | 0.1378 |
| 2020-21 | Skellefteå AIK U20 | SuperElit | 15 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | Maine Nordiques | NAHL | 43 | 7 | 9 | 16 | 0.372 | 0.1367 | 0.1371 | 0.3933 | 0.3945 |
| 2022-23 | Maine Nordiques | NAHL | 60 | 17 | 32 | 49 | 0.817 | 0.3001 | 0.2863 | 0.8632 | 0.8234 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Alaska Fairbanks | D1 | WCHA | — | 3 | 1 | 0 | 1 | 0.333 |
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.