| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Rögle BK U20 | SuperElit | 5 | 0 | 1 | 1 | 0.200 | 0.0789 | 0.0879 | 0.2716 | 0.3027 |
| 2015-16 | Rögle BK U20 | SHL-J20 | 35 | 7 | 8 | 15 | 0.429 | 0.2382 | 0.2539 | 0.5711 | 0.6087 |
| 2016-17 | Rögle BK U20 | SuperElit | 39 | 11 | 23 | 34 | 0.872 | 0.3440 | 0.3533 | 1.1840 | 1.2162 |
| 2017-18 | Rögle BK U20 | SuperElit | 35 | 10 | 23 | 33 | 0.943 | 0.3721 | 0.3584 | 1.2806 | 1.2335 |
| 2018-19 | Sioux City Musketeers | USHL | 60 | 9 | 13 | 22 | 0.367 | 0.2163 | 0.1994 | 1.1013 | 1.0152 |
| 2024-25 | Kalmar HC | Allsvenskan | 47 | 4 | 8 | 12 | 0.255 | 0.6383 | 0.6158 | 2.3952 | 2.3108 |
| 2025-26 | IF Troja-Ljungby | Allsvenskan | 49 | 11 | 15 | 26 | 0.531 | 1.3265 | 1.3203 | 4.9780 | 4.9546 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Miami | D1 | NCHC | — | 17 | 4 | 5 | 9 | 0.529 |
| 2022-23 | Niagara | D1 | AHA | — | 40 | 10 | 14 | 24 | 0.600 |
| 2021-22 | Niagara | D1 | AHA | — | 32 | 8 | 13 | 21 | 0.656 |
| 2020-21 | Providence | D1 | HockeyEast | SO | 12 | 1 | 0 | 1 | 0.083 |
| 2019-20 | Providence | D1 | HockeyEast | FR | 22 | 0 | 5 | 5 | 0.227 |
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.