icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NAHL | 34 | 18 | 9 | 91.9% | 1.99 | 2 | 0.9843 | 86.9% |
| 2021-22 | — | Allsvenskan | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | SuperElit | 21 | 9 | 9 | 88.9% | 3.61 | 2 | 0.9600 | 81.9% |
| 2021-22 | — | SHL-J20 | 21 | 9 | 9 | 88.9% | 3.61 | 2 | 0.9600 | 81.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Northern Michigan | D1 | 18 | 1 | 15 | 89.4% | 4.25 | 0 |
| 2024-25 | Wisconsin | D1 | 8 | 2 | 4 | 87.8% | 3.23 | 0 |
| 2023-24 | Wisconsin | D1 | 4 | 2 | 0 | 95.9% | 1.13 | 1 |
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 |
|---|---|---|---|---|---|---|
| Owen Say | BCHL | 92.3% | 87.2% | Mercyhurst | 90.3% | 3.39 |
| Justen Close | SJHL | 92.8% | 86.0% | Minnesota | 78.6% | 6.09 |
| Noah Pak | OJHL | 94.5% | 86.1% | Yale | 87.2% | 3.86 |
| Jacob Steinman | QMJHL | 92.3% | 85.4% | Bowling Green | 92.1% | 2.14 |
| Cooper Black | BCHL | 92.4% | 87.4% | Dartmouth | 89.9% | 3.07 |
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 |
|---|---|---|---|---|---|---|---|
| Colby Muise | AJHL | 91.6% | 86.8% | Marian | D3 | 93.2% | 1.77 |
| Matthew Malin | AJHL | 90.7% | 86.5% | St. Olaf | D3 | 90.6% | 2.47 |
| Will Augustine | USPHL-Premier | 94.0% | 86.5% | Rivier | D3 | 91.5% | 2.97 |
| Jadon Lee | USPHL-Premier | 93.3% | 86.0% | Lebanon Valley | D3 | 93.0% | 2.59 |
| Cam Prodin | USPHL-Premier | 93.6% | 86.0% | Roger Williams | D3 | 75.8% | 9.18 |
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.