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 | El Paso Rhinos | NAHL | 6 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | El Paso Rhinos | NAHL | 3 | 2 | 1 | 3 | 1.000 | 0.3674 | 0.4120 | 1.0569 | 1.1852 |
| 2024-25 | Dubuque Fighting Saints | USHL | 50 | 10 | 13 | 23 | 0.460 | 0.2714 | 0.2781 | 1.3803 | 1.4146 |
| 2025-26 | Erie Otters | OHL | 61 | 6 | 4 | 10 | 0.164 | 0.0948 | 0.0923 | 0.4292 | 0.4179 |
| 2026-27 | Green Bay Gamblers | USHL | 4 | 0 | 1 | 1 | 0.250 | 0.1475 | 0.1475 | 0.7502 | 0.7502 |
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.