icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Pittsburgh Penguins
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2009-10 | Penticton Vees | BCHL | 56 | 41 | 79 | 120 | 2.143 | 0.8257 | 0.8663 | 3.1186 | 3.2721 |
| 2018-19 | Dinamo Minsk | KHL | 5 | 0 | 1 | 1 | 0.200 | 0.5000 | 0.5108 | 2.7557 | 2.8151 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Denver | D1 | WCHA-orig | SO | 10 | 4 | 9 | 13 | 1.300 |
| 2010-11 | Denver | D1 | WCHA-orig | FR | 37 | 9 | 16 | 25 | 0.676 |
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.