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 | South Shore Kings | NCDC | 41 | 2 | 17 | 19 | 0.463 | 0.1071 | 0.1096 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Lake Forest | D3 | NCHA | SR | 1 | 0 | 0 | 0 | 0.000 |
| 2024-25 | Lake Forest | D3 | NCHA | JR | 12 | 0 | 1 | 1 | 0.083 |
| 2023-24 | Lake Forest | D3 | NCHA | SO | 23 | 2 | 3 | 5 | 0.217 |
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.