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 | Elk River/Zimmerman | USHS-MN | 20 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Elk River/Zimmerman | USHS-MN | 12 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | Elk River/Zimmerman | USHS-MN | 31 | 3 | 5 | 8 | 0.258 | 0.0327 | 0.0327 | 0.0627 | 0.0627 |
| 2025-26 | U.S. National U17 Team | NTDP-U18 | 47 | 3 | 14 | 17 | 0.362 | 0.2689 | 0.2782 | 1.3496 | 1.3962 |
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.