icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
No junior season data found for this player.
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Plattsburgh State | D3 | 14 | 9 | 4 | 90.4% | 1.79 | 4 |
| 2024-25 | Plattsburgh State | D3 | 28 | 20 | 7 | 95.3% | 0.89 | 11 |
| 2023-24 | Plattsburgh State | D3 | 5 | 4 | 0 | 96.2% | 0.86 | 1 |
| 2023-24 | Elmira | D3 | 15 | 11 | 2 | 96.0% | 0.78 | 6 |
| 2022-23 | Plattsburgh State | D3 | 3 | 1 | 0 | 100.0% | — | 1 |
| 2021-22 | Plattsburgh State | D3 | 14 | 12 | 1 | 92.6% | 1.67 | 3 |
| 2019-20 | Plattsburgh State | D3 | 4 | 3 | 1 | 93.7% | 1.17 | 1 |
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.