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 | Fargo Force | USHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2023-24 | Jersey Hitmen | NCDC | 52 | 11 | 16 | 27 | 0.519 | 0.2117 | 0.2306 | 0.4155 | 0.4526 |
| 2024-25 | Maryland Black Bears | NAHL | 41 | 7 | 3 | 10 | 0.244 | 0.0896 | 0.0934 | 0.2578 | 0.2686 |
| 2025-26 | Sioux Falls Stampede | USHL | 55 | 7 | 10 | 17 | 0.309 | 0.1823 | 0.1731 | 0.9275 | 0.8808 |
| 2026-27 | Brooks Bandits | BCHL | 5 | 2 | 1 | 3 | 0.600 | 0.2312 | 0.2312 | 0.8726 | 0.8726 |
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.