icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | EHL | 28 | 22 | 4 | 95.9% | 1.05 | 10 | 0.9400 | 87.6% |
| 2020-21 | — | EHL | 23 | 21 | 2 | 94.8% | 1.60 | 5 | 0.9400 | 89.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Babson | D3 | 21 | — | — | 92.5% | 1.88 | 1 |
| 2024-25 | Babson | D3 | 14 | 8 | 5 | 93.5% | 1.98 | 1 |
| 2023-24 | Babson | D3 | 13 | 7 | 6 | 90.0% | 3.10 | 1 |
| 2022-23 | Babson | D3 | 5 | 2 | 3 | 91.7% | 2.75 | — |
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 |
|---|---|---|---|---|---|---|
| Jackson Fuller | NAHL | 92.9% | 86.2% | Northern Michigan | — | — |
| Gergely Orosz | NAHL | 91.9% | 85.4% | Alaska Anchorage | 91.5% | 2.75 |
| Tomas Anderson | NAHL | 93.7% | 87.7% | Niagara | 89.0% | 3.20 |
| Beni Halasz | NAHL | 92.1% | 85.2% | Northern Michigan | 91.9% | 2.32 |
| Klayton Knapp | NAHL | 92.1% | 86.5% | Minnesota Duluth | 90.7% | 2.67 |
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 |
|---|---|---|---|---|---|---|---|
| Ryan Hacker | EHL | 91.6% | 87.3% | Wilkes | D3 | 66.7% | 5.16 |
| Liam Kilgallen | EHL | 90.8% | 87.0% | Framingham State | D3 | 86.4% | 4.74 |
| Matthew O'Donnell | NCDC | 92.6% | 87.9% | Aurora | D3 | 91.0% | 2.97 |
| Frank Murphy | NAHL | 92.3% | 88.3% | Utica | D3 | 89.7% | 2.23 |
| Damon Beaver | NAHL | 91.4% | 87.6% | Hobart | D3 | 95.5% | 1.04 |
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.