icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2010-11 | Segeltorps IF | SDHL | 28 | 3 | 9 | 12 | 0.429 | 0.4950 | 0.6021 | — | — |
| 2011-12 | Segeltorps IF | SDHL | 28 | 2 | 3 | 5 | 0.179 | 0.2063 | 0.2379 | — | — |
| 2012-13 | AIK | SDHL | 24 | 1 | 3 | 4 | 0.167 | 0.1925 | 0.2193 | — | — |
| 2013-14 | AIK | SDHL | 26 | 1 | 5 | 6 | 0.231 | 0.2666 | 0.2981 | — | — |
| 2018-19 | AIK | SDHL | 30 | 2 | 7 | 9 | 0.300 | 0.3465 | 0.3320 | — | — |
| 2019-20 | AIK | SDHL | 36 | 5 | 2 | 7 | 0.194 | 0.2245 | 0.2245 | — | — |
| 2020-21 | AIK | SDHL | 35 | 2 | 5 | 7 | 0.200 | 0.2310 | 0.2310 | — | — |
| 2021-22 | AIK | SDHL | 33 | 0 | 2 | 2 | 0.061 | 0.0700 | 0.0579 | — | — |
| 2023-24 | SDE HF | SDHL | 5 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Minnesota Duluth | D1 | WCHA-W | — | 35 | 0 | 5 | 5 | 0.143 |
| 2016-17 | Minnesota Duluth | D1 | WCHA-W | — | 37 | 2 | 5 | 7 | 0.189 |
| 2015-16 | Minnesota Duluth | D1 | WCHA-W | — | 35 | 1 | 3 | 4 | 0.114 |
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.