icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | — | CCHL | 12 | 6 | 5 | 87.0% | 3.31 | 0 | 0.9700 | 84.4% |
| 2018-19 | — | CCHL | 22 | 12 | 5 | 90.7% | 2.51 | 1 | 0.9700 | 97.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Castleton | D3 | 13 | — | — | 91.4% | 2.73 | 2 |
| 2024-25 | Castleton | D3 | 17 | 4 | 10 | 88.5% | 3.93 | 1 |
| 2023-24 | Castleton | D3 | 8 | 2 | 4 | 84.2% | 4.92 | 0 |
| 2022-23 | Castleton | D3 | 3 | 1 | 1 | 87.0% | 4.29 | — |
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 |
|---|---|---|---|---|---|---|
| Tyler Muszelik | USHL | 90.0% | 97.4% | New Hampshire | 88.3% | 3.24 |
| Jack Ivankovic | OHL | 90.3% | 96.9% | Michigan | 92.1% | 2.15 |
| Spencer Knight | USHL | 90.3% | 96.6% | Boston College | 93.1% | 1.97 |
| Trey Augustine | USHL | 92.8% | 97.9% | Michigan State | 91.5% | 2.96 |
| Mikhail Yegorov | USHL | 89.2% | 94.4% | Boston University | 92.7% | 2.15 |
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 |
|---|---|---|---|---|---|---|---|
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Cooper Rautenstrauch | NAHL | 88.9% | 94.0% | Colby | D3 | 93.4% | 2.08 |
| Vaughn Makar | NAHL | 90.9% | 95.6% | St. Norbert | D3 | 93.2% | 1.73 |
| Cooper Rautenstrauch | NCDC | 90.6% | 93.8% | Colby | D3 | 93.4% | 2.08 |
| Brayden Ingram | EHL | 91.2% | 94.4% | Assumption | D2 | 91.4% | 2.71 |
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.