icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Djurgårdens IF | SDHL | 5 | 2 | 1 | 3 | 0.600 | 0.6930 | 0.6971 | — | — |
| 2018-19 | Leksands IF | SDHL | 34 | 11 | 8 | 19 | 0.559 | 0.6454 | 0.6247 | — | — |
| 2019-20 | MoDo Hockey | SDHL | 35 | 8 | 11 | 19 | 0.543 | 0.6270 | 0.6270 | — | — |
| 2020-21 | Linköping HC | SDHL | 36 | 5 | 7 | 12 | 0.333 | 0.3850 | 0.3850 | — | — |
| 2021-22 | Leksands IF | SDHL | 36 | 6 | 6 | 12 | 0.333 | 0.3850 | 0.3223 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | North Dakota | D1 | — | — | 37 | 5 | 13 | 18 | 0.486 |
| 2015-16 | North Dakota | D1 | — | — | 35 | 4 | 5 | 9 | 0.257 |
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.