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 |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Post | D1 | CHA-W | SR | 35 | 5 | 7 | 12 | 0.343 |
| 2025-26 | Post | D3 | — | SR | 35 | 5 | 7 | 12 | 0.343 |
| 2024-25 | Post | D1 | CHA-W | JR | 22 | 2 | 2 | 4 | 0.182 |
| 2024-25 | Post | D3 | — | JR | 20 | 2 | 2 | 4 | 0.200 |
| 2023-24 | Post | D1 | CHA-W | SO | 36 | 3 | 10 | 13 | 0.361 |
| 2023-24 | Post | D3 | — | SO | 30 | 2 | 7 | 9 | 0.300 |
| 2022-23 | Post | D1 | CHA-W | FR | 31 | 4 | 7 | 11 | 0.355 |
| 2022-23 | Post | D3 | — | FR | 15 | 0 | 3 | 3 | 0.200 |
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.