icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | NAHL | 38 | 10 | 20 | 90.0% | 3.84 | 2 | 0.9843 | 81.6% |
| 2020-21 | — | NAHL | 20 | 8 | 8 | 90.7% | 3.43 | 0 | 0.9843 | 89.3% |
| 2019-20 | — | NTDP-U18 | 1 | 1 | 0 | 82.8% | 5.00 | 0 | 0.9200 | 76.2% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Skidmore | D3 | 8 | — | — | 91.9% | 2.52 | 0 |
| 2024-25 | Skidmore | D3 | 19 | 12 | 7 | 90.5% | 2.50 | 1 |
| 2023-24 | Bentley | D1 | — | — | — | — | — | — |
| 2022-23 | Bentley | D1 | 1 | 0 | 0 | 82.6% | 8.58 | 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 |
|---|---|---|---|---|---|---|
| Austin Roden | BCHL | 91.2% | 81.1% | Nebraska Omaha | 90.7% | 2.87 |
| David Fessenden | NAHL | 91.5% | 82.6% | Alabama-Huntsville | 86.9% | 4.44 |
| Justen Close | SJHL | 92.8% | 82.4% | Minnesota | 78.6% | 6.09 |
| Noah Pak | OJHL | 94.5% | 81.2% | Yale | 87.2% | 3.86 |
| Salvatore Evola | NAHL | 91.7% | 82.9% | Bowling Green | 86.2% | 4.25 |
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% | 81.9% | Marian | D3 | 93.2% | 1.77 |
| Jadon Lee | USPHL-Premier | 93.3% | 82.1% | Lebanon Valley | D3 | 93.0% | 2.59 |
| Will Augustine | USPHL-Premier | 94.0% | 82.5% | Rivier | D3 | 91.5% | 2.97 |
| Josh Koziol | NA3HL | 93.3% | 81.2% | Augsburg | D3 | 71.4% | 5.76 |
| Jacob Gorinsky | OJHL | 89.9% | 80.7% | Norwich | D3 | 83.3% | 5.00 |
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.