| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Djurgårdens IF U20 | SuperElit | 36 | 3 | 15 | 18 | 0.500 | 0.1973 | 0.2138 | 0.6791 | 0.7358 |
| 2015-16 | Omaha Lancers | USHL | 44 | 5 | 8 | 13 | 0.295 | 0.1743 | 0.1818 | 0.8875 | 0.9257 |
| 2016-17 | Djurgårdens IF U20 | SHL-J20 | 19 | 2 | 10 | 12 | 0.632 | 0.3510 | 0.3446 | 0.8415 | 0.8262 |
| 2017-18 | Fargo Force | USHL | 58 | 14 | 31 | 45 | 0.776 | 0.4577 | 0.4313 | 2.3303 | 2.1959 |
| 2020-21 | — | Allsvenskan | 47 | 7 | 8 | 15 | 0.319 | 0.7977 | 0.7977 | 2.9938 | 2.9938 |
| 2021-22 | HC Vita Hästen | Allsvenskan | 15 | 0 | 1 | 1 | 0.067 | 0.1667 | 0.1797 | 0.6258 | 0.6746 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Quinnipiac | D1 | ECAC | SO | 33 | 1 | 16 | 17 | 0.515 |
| 2018-19 | Quinnipiac | D1 | ECAC | FR | 38 | 8 | 13 | 21 | 0.553 |
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.