icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | HV71 U20 | SuperElit | 5 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | HV71 U20 | SuperElit | 46 | 6 | 19 | 25 | 0.543 | 0.2145 | 0.2320 | 0.7381 | 0.7983 |
| 2023-24 | HV71 U20 | SuperElit | 34 | 4 | 10 | 14 | 0.412 | 0.1625 | 0.1663 | 0.5593 | 0.5722 |
| 2024-25 | Green Bay Gamblers | USHL | 6 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2025-26 | — | BCHL | 54 | 7 | 36 | 43 | 0.796 | 0.3068 | 0.2965 | 1.1589 | 1.1201 |
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.