icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2003-04 | Pembroke Lumber Kings | CCHL | 55 | 13 | 17 | 30 | 0.545 | 0.1742 | 0.1891 | 0.4223 | 0.4585 |
| 2004-05 | Pembroke Lumber Kings | CCHL | 49 | 25 | 39 | 64 | 1.306 | 0.4170 | 0.4345 | 1.0111 | 1.0535 |
| 2005-06 | Pembroke Lumber Kings | CCHL | 56 | 70 | 77 | 147 | 2.625 | 0.8382 | 0.8363 | 2.0320 | 2.0274 |
| 2010-11 | Södertälje SK | SHL | 55 | 12 | 18 | 30 | 0.545 | 1.3638 | 1.5445 | — | — |
| 2011-12 | Pelicans | Liiga | 59 | 24 | 38 | 62 | 1.051 | 2.6270 | 2.8192 | — | — |
| 2012-13 | Växjö Lakers HC | SHL | 10 | 0 | 5 | 5 | 0.500 | 1.2500 | 1.2879 | — | — |
| 2013-14 | Växjö Lakers HC | SHL | 54 | 20 | 16 | 36 | 0.667 | 1.6667 | 1.5967 | — | — |
| 2014-15 | TPS | Liiga | 43 | 12 | 24 | 36 | 0.837 | 2.0930 | 1.9322 | — | — |
| 2015-16 | Frölunda HC | SHL | 51 | 15 | 36 | 51 | 1.000 | 2.5000 | 2.1323 | — | — |
| 2017-18 | Frölunda HC | SHL | 49 | 15 | 40 | 55 | 1.122 | 2.8060 | 2.1389 | — | — |
| 2018-19 | Frölunda HC | SHL | 46 | 12 | 38 | 50 | 1.087 | 2.7175 | 1.9363 | — | — |
| 2019-20 | Frölunda HC | SHL | 48 | 12 | 36 | 48 | 1.000 | 2.5000 | 2.5000 | — | — |
| 2020-21 | Pelicans | Liiga | 26 | 10 | 27 | 37 | 1.423 | 3.5577 | 3.5577 | — | — |
| 2021-22 | Frölunda HC | SHL | 52 | 13 | 53 | 66 | 1.269 | 3.1730 | 1.8688 | — | — |
| 2022-23 | Frölunda HC | SHL | 41 | 5 | 19 | 24 | 0.585 | 1.4635 | 0.8273 | — | — |
| 2023-24 | Pelicans | Liiga | 55 | 9 | 45 | 54 | 0.982 | 2.4545 | 1.2272 | — | — |
| 2024-25 | Pelicans | Liiga | 54 | 13 | 39 | 52 | 0.963 | 2.4075 | 1.2038 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2009-10 | St. Cloud State | D1 | — | SR | 43 | 20 | 29 | 49 | 1.139 |
| 2008-09 | St. Cloud State | D1 | — | JR | 38 | 18 | 24 | 42 | 1.105 |
| 2007-08 | St. Cloud State | D1 | — | SO | 40 | 25 | 28 | 53 | 1.325 |
| 2006-07 | St. Cloud State | D1 | — | FR | 40 | 16 | 23 | 39 | 0.975 |
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.