| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Örebro HK U20 | SuperElit | 43 | 11 | 23 | 34 | 0.791 | 0.3044 | 0.3371 | 1.0279 | 1.1383 |
| 2023-24 | Örebro HK U20 | SuperElit | 45 | 21 | 37 | 58 | 1.289 | 0.4962 | 0.5233 | 1.6756 | 1.7671 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Minnesota | D1 | BigTen | — | 39 | 7 | 10 | 17 | 0.436 |
| 2024-25 | Boston University | D1 | HockeyEast | — | 24 | 5 | 3 | 8 | 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.