icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | NAHL | 41 | 18 | 18 | 92.3% | 2.72 | 2 | 0.9843 | 88.2% |
| 2023-24 | — | NCDC | 27 | 19 | 5 | 93.3% | 2.12 | 5 | 0.9400 | 88.2% |
| 2023-24 | — | BCHL | 3 | 2 | 0 | 89.9% | 3.18 | 0 | 0.9990 | 89.4% |
| 2022-23 | — | USPHL-Premier | 31 | 25 | 4 | 92.7% | 1.82 | 6 | 0.9400 | 90.4% |
| 2021-22 | — | USPHL-Premier | 19 | 13 | 3 | 94.0% | 1.80 | 3 | 0.9400 | 94.8% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Utica | D3 | 8 | — | — | 89.7% | 2.23 | 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 |
|---|---|---|---|---|---|---|
| John Hawthorne | BCHL | 91.8% | 87.6% | Northern Michigan | 88.2% | 3.10 |
| Gergely Orosz | NAHL | 91.9% | 87.8% | Alaska Anchorage | 91.5% | 2.75 |
| Jackson Fuller | NAHL | 92.9% | 88.7% | Northern Michigan | — | — |
| Beni Halasz | NAHL | 92.1% | 87.8% | Northern Michigan | 91.9% | 2.32 |
| Klayton Knapp | NAHL | 92.1% | 88.5% | 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 |
|---|---|---|---|---|---|---|---|
| Nolan Suggs | NAHL | 90.1% | 88.6% | Adrian | D3 | 92.4% | 1.75 |
| Liam Kilgallen | EHL | 90.8% | 88.2% | Framingham State | D3 | 86.4% | 4.74 |
| Jacob Jaslow | NCDC | 90.7% | 88.1% | Roger Williams | D3 | 91.0% | 3.49 |
| Tyler Roy | EHL | 91.3% | 87.9% | Neumann | D3 | 87.2% | 3.68 |
| Ryan Hacker | EHL | 91.6% | 88.7% | Wilkes | D3 | 66.7% | 5.16 |
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.