icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
New Jersey Devils
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | TPS | Liiga | 42 | 4 | 12 | 16 | 0.381 | 0.9525 | 1.0254 | 3.2751 | 3.5257 |
| 2024-25 | TPS | Liiga | 60 | 2 | 5 | 7 | 0.117 | 0.2918 | 0.3039 | 1.0032 | 1.0449 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Penn State | D1 | BigTen | JR | 21 | 7 | 6 | 13 | 0.619 |
| 2019-20 | Penn State | D1 | BigTen | SO | 30 | 6 | 13 | 19 | 0.633 |
| 2018-19 | Penn State | D1 | BigTen | FR | 17 | 5 | 11 | 16 | 0.941 |
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.