icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | Jokerit | Liiga | 55 | 22 | 16 | 38 | 0.691 | 1.7272 | 2.0207 | — | — |
| 2013-14 | Jokerit | Liiga | 42 | 12 | 11 | 23 | 0.548 | 1.3690 | 1.5516 | — | — |
| 2014-15 | Jokerit | KHL | 60 | 36 | 21 | 57 | 0.950 | 2.3750 | 2.6192 | — | — |
| 2015-16 | SKA St. Petersburg | KHL | 21 | 10 | 6 | 16 | 0.762 | 1.9047 | 1.9721 | — | — |
| 2016-17 | SKA St. Petersburg | KHL | 24 | 3 | 7 | 10 | 0.417 | 1.0417 | 1.0350 | — | — |
| 2017-18 | Jokerit | KHL | 13 | 4 | 1 | 5 | 0.385 | 0.9615 | 0.9143 | — | — |
| 2018-19 | Jokerit | KHL | 59 | 15 | 25 | 40 | 0.678 | 1.6950 | 1.5367 | — | — |
| 2019-20 | Jokerit | KHL | 43 | 7 | 10 | 17 | 0.395 | 0.9882 | 0.9882 | — | — |
| 2022-23 | HPK | Liiga | 55 | 13 | 17 | 30 | 0.545 | 1.3638 | 0.8630 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | New Hampshire | D1 | HockeyEast | — | 37 | 22 | 13 | 35 | 0.946 |
| 2010-11 | New Hampshire | D1 | HockeyEast | — | 39 | 14 | 12 | 26 | 0.667 |
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.