icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Groton | NE-Prep | 25 | 0 | 1 | 1 | 0.040 | 0.0080 | 0.0080 | 0.0183 | 0.0183 |
| 2023-24 | Groton | NE-Prep | 26 | 3 | 9 | 12 | 0.462 | 0.0928 | 0.0928 | 0.2110 | 0.2110 |
| 2024-25 | Groton | NE-Prep | 27 | 3 | 4 | 7 | 0.259 | 0.0521 | 0.0521 | — | — |
| 2025-26 | Lincoln Stars | USHL | 5 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2026-27 | Sherbrooke Phoenix | QMJHL | 4 | 0 | 0 | 0 | 0.000 | — | — | — | — |
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.