icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | P.A.L. Junior Islanders | NCDC | 52 | 16 | 16 | 32 | 0.615 | 0.2509 | 0.2632 | 0.4924 | 0.5165 |
| 2024-25 | P.A.L. Junior Islanders | NCDC | 54 | 31 | 30 | 61 | 1.130 | 0.4605 | 0.4626 | 0.9039 | 0.9080 |
| 2025-26 | Youngstown Phantoms | USHL | 5 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | Canisius | D1 | AHA | FR | 0 | 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.