icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | SM-Liiga-Jr | 12 | 9 | 2 | 91.2% | 1.98 | 0 | 0.9600 | 85.5% |
| 2020-21 | — | SM-Liiga-Jr | 15 | — | — | 86.6% | 3.67 | — | 0.9600 | 83.1% |
| 2019-20 | — | SM-Liiga-Jr | 19 | — | — | 85.4% | — | — | 0.9600 | 82.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan Tech | D1 | 1 | 0 | 1 | 85.7% | 5.06 | 0 |
| 2024-25 | Michigan Tech | D1 | 4 | 3 | 1 | 92.0% | 1.74 | 0 |
| 2023-24 | Michigan Tech | D1 | 4 | 1 | 2 | 89.7% | 2.40 | 0 |
| 2022-23 | Michigan Tech | D1 | 4 | 1 | 0 | 90.3% | 2.32 | 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 |
|---|---|---|---|---|---|---|
| Matej Marinov | USHL | 91.7% | 85.9% | Quinnipiac | 91.3% | 1.85 |
| Ryan Bischel | USHL | 90.5% | 85.5% | Notre Dame | 91.5% | 2.52 |
| Cameron Whitehead | USHL | 90.4% | 84.7% | Northeastern | 91.7% | 2.62 |
| Evan Fear | USHL | 90.8% | 85.7% | Quinnipiac | 77.4% | 6.56 |
| Jack Stark | USHL | 90.0% | 84.4% | Yale | 91.9% | 2.22 |
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 |
|---|---|---|---|---|---|---|---|
| Tyler Fromolz | NA3HL | 92.0% | 87.1% | Marian | D3 | 88.3% | 3.85 |
| Jarret Bovarnick | EHL | 88.3% | 87.8% | Suffolk | D3 | 87.2% | 4.52 |
| Andrew Doran | NA3HL | 93.4% | 87.1% | Utica | D3 | 100.0% | — |
| Russ Decoste | USPHL-Premier | 93.1% | 87.0% | Westfield State | D3 | 93.3% | 2.38 |
| Jackson Fellner | SJHL | 89.9% | 85.7% | Alvernia | D3 | 92.4% | 2.68 |
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.