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 | Dauphin Kings | MJHL | 63 | 32 | 33 | 65 | 1.032 | 0.1986 | 0.2205 | 0.6506 | 0.7224 |
| 2004-05 | Lincoln Stars | USHL | 60 | 20 | 38 | 58 | 0.967 | 0.5703 | 0.5972 | 2.9034 | 3.0401 |
| 2010-11 | Dinamo Riga | KHL | 49 | 9 | 17 | 26 | 0.531 | 1.3265 | 1.5673 | 7.3110 | 8.6380 |
| 2014-15 | — | KHL | 32 | 2 | 6 | 8 | 0.250 | 0.6250 | 0.6092 | 3.4447 | 3.3574 |
| 2015-16 | IF Björklöven | Allsvenskan | 35 | 6 | 20 | 26 | 0.743 | 1.8573 | 1.5078 | 6.9698 | 5.6581 |
| 2016-17 | — | Liiga | 42 | 12 | 19 | 31 | 0.738 | 1.8453 | 1.5257 | 6.3448 | 5.2459 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2007-08 | Denver | D1 | NCHC | SO | 24 | 13 | 18 | 31 | 1.292 |
| 2006-07 | Denver | D1 | NCHC | FR | 40 | 16 | 24 | 40 | 1.000 |
| 2005-06 | Denver | D1 | NCHC | FR | 5 | 3 | 2 | 5 | 1.000 |
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.