icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | EHL | 20 | 15 | 4 | 92.2% | 2.56 | 2 | 0.9400 | 80.9% |
| 2023-24 | — | EHL | 37 | 16 | 14 | 92.4% | 3.05 | 2 | 0.9400 | 87.3% |
| 2022-23 | — | USPHL-Premier | 1 | 0 | 1 | 95.1% | 2.00 | 0 | 0.9400 | 92.5% |
| 2021-22 | — | NCDC | — | — | — | — | — | — | 0.9400 | — |
| 2021-22 | — | NAHL | — | — | — | — | — | — | 0.9843 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Keene State | D3 | 5 | — | — | 86.4% | 5.61 | 0 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D1.
| Name | Junior League | Junior SV% | Adj SVe | College | NCAA SV% | NCAA GAA |
|---|---|---|---|---|---|---|
| Henry Levy | BCHL | 91.8% | 80.8% | Arizona State | 100.0% | — |
| Cole Plowman | MJHL | 93.4% | 80.7% | Alaska Fairbanks | 100.0% | — |
| Eli Pulver | BCHL | 92.4% | 81.7% | Minnesota | 95.8% | 1.00 |
| Kayden Hargraves | NAHL | 91.5% | 81.8% | Augustana | 92.0% | 2.72 |
| Andrew Takacs | NAHL | 91.8% | 82.0% | Colgate | 81.8% | 4.32 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D2/D3.
| Name | Junior League | Junior SV% | Adj SVe | College | Div | SV% | GAA |
|---|---|---|---|---|---|---|---|
| Matthew Dore | USPHL-Premier | 94.4% | 80.9% | Rivier | D3 | 88.8% | 4.78 |
| Jeffrey Fillion | NCDC | 89.6% | 81.6% | Wilkes | D3 | 92.4% | 1.96 |
| Sebastian Woods | NCDC | 90.6% | 81.9% | Manhattanville | D3 | 91.4% | 3.07 |
| Ford DeLoss | NCDC | 90.0% | 82.1% | Stevenson | D3 | 88.9% | 3.00 |
| Logan Gorbitz | USPHL-Premier | 91.8% | 79.4% | Neumann | D3 | 84.4% | 5.24 |
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.