icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | MJHL | 39 | 30 | 6 | 93.4% | 1.81 | 4 | 0.9700 | 80.7% |
| 2022-23 | — | MJHL | 24 | 17 | 6 | 91.3% | 2.33 | 3 | 0.9700 | 85.4% |
| 2021-22 | — | MJHL | 29 | 13 | 11 | 89.5% | 3.32 | 0 | 0.9700 | 89.4% |
| 2020-21 | — | MJHL | 3 | 0 | 3 | 88.3% | 4.35 | 0 | 0.9700 | 85.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | Alaska Fairbanks | D1 | 1 | 0 | 0 | 100.0% | — | 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% | — |
| Charles-Edward Gravel | BCHL | 93.0% | 82.6% | Mercyhurst | 90.7% | 3.22 |
| Eli Pulver | BCHL | 92.4% | 81.7% | Minnesota | 95.8% | 1.00 |
| Carter Clafton | NAHL | 91.9% | 82.5% | Air Force | 100.0% | — |
| Austin Roden | BCHL | 91.2% | 81.1% | Nebraska Omaha | 90.7% | 2.87 |
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 |
|---|---|---|---|---|---|---|---|
| Cameron Hrdlicka | SJHL | 89.6% | 79.6% | Concordia | D3 | 89.0% | 3.97 |
| Matthew Dore | USPHL-Premier | 94.4% | 80.9% | Rivier | D3 | 88.8% | 4.78 |
| Blake Carlson | USPHL-Premier | 94.7% | 82.0% | Framingham State | D3 | 91.9% | 3.26 |
| Logan Palmer | USPHL-Premier | 92.1% | 80.5% | Western New England | D3 | 90.9% | 3.11 |
| Sebastian Woods | NCDC | 90.6% | 81.9% | Manhattanville | D3 | 91.4% | 3.07 |
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.