icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Skellefteå AIK U20 | SuperElit | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2015-16 | Skellefteå AIK U20 | SHL-J20 | 39 | 7 | 9 | 16 | 0.410 | 0.2280 | 0.2268 | 0.5467 | 0.5438 |
| 2016-17 | Skellefteå AIK U20 | SHL-J20 | 27 | 6 | 11 | 17 | 0.630 | 0.3499 | 0.3295 | 0.8389 | 0.7899 |
| 2017-18 | Madison Capitols | USHL | 60 | 17 | 24 | 41 | 0.683 | 0.4031 | 0.3637 | 2.0522 | 1.8515 |
| 2021-22 | HC Vita Hästen | Allsvenskan | 52 | 7 | 18 | 25 | 0.481 | 1.2020 | 1.2475 | 4.5108 | 4.6816 |
| 2022-23 | Västerviks IK | Allsvenskan | 46 | 11 | 11 | 22 | 0.478 | 1.1958 | 1.1739 | 4.4874 | 4.4052 |
| 2023-24 | Kalmar HC | Allsvenskan | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Niagara | D1 | AHA | JR | 17 | 7 | 7 | 14 | 0.824 |
| 2019-20 | Niagara | D1 | AHA | SO | 16 | 5 | 5 | 10 | 0.625 |
| 2018-19 | Niagara | D1 | AHA | FR | 41 | 23 | 19 | 42 | 1.024 |
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.