icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
No junior season data found for this player.
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Maine | D1 | HEA-W | GR | 32 | 1 | 4 | 5 | 0.156 |
| 2022-23 | LIU | D1 | CHA-W | SR | 35 | 9 | 13 | 22 | 0.629 |
| 2022-23 | Long Island Univ. | D1 | CHA-W | SR | 35 | 9 | 13 | 22 | 0.629 |
| 2021-22 | Long Island Univ. | D1 | CHA-W | JR | 32 | 7 | 9 | 16 | 0.500 |
| 2020-21 | Long Island Univ. | D1 | CHA-W | SO | 13 | 3 | 2 | 5 | 0.385 |
| 2019-20 | Long Island Univ. | D1 | CHA-W | FR | 32 | 10 | 11 | 21 | 0.656 |
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.