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 | 15 | 4 | 7 | 90.5% | 2.57 | 0 | 0.9843 | 86.5% |
| 2021-22 | — | NCDC | 1 | 1 | 0 | 86.7% | 3.00 | 0 | 0.9400 | 81.8% |
| 2021-22 | — | NAHL | 25 | 5 | 14 | 86.1% | 4.18 | 1 | 0.9843 | 85.3% |
| 2020-21 | — | NAHL | 21 | 9 | 7 | 91.0% | 2.54 | 1 | 0.9843 | 89.6% |
| 2020-21 | — | NTDP-U18 | 1 | 1 | 0 | 86.4% | 2.87 | 0 | 0.9200 | 79.5% |
| 2020-21 | — | USHL | 1 | 1 | 0 | 86.4% | 2.87 | 0 | 0.9983 | 86.2% |
| 2018-19 | — | USHL | 2 | 0 | 0 | 85.7% | 3.38 | 0 | 0.9983 | 93.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Skidmore | D3 | 15 | 9 | 4 | 91.6% | 2.55 | 0 |
| 2024-25 | Skidmore | D3 | 9 | 2 | 4 | 89.5% | 3.01 | 1 |
| 2023-24 | Stevenson | D3 | — | — | — | — | — | — |
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 |
|---|---|---|---|---|---|---|
| Rorke Applebee | BCHL | 90.2% | 86.5% | Lake Superior State | 90.7% | 3.00 |
| 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 |
| Malachi Klassen | MJHL | 91.7% | 85.4% | Holy Cross | — | 3.04 |
| Connor Murphy | CCHL | 91.7% | 84.9% | Northeastern | 68.8% | 7.04 |
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 |
|---|---|---|---|---|---|---|---|
| Duncan Rolleman | USPHL-Premier | 92.5% | 86.2% | Wilkes | D3 | 90.0% | 3.84 |
| Tyler Sayger | NCDC | 89.4% | 86.1% | King's | D3 | 90.5% | 4.40 |
| Jeff Zero | NA3HL | 95.0% | 85.9% | Elmira | D3 | 100.0% | — |
| Matthew O'Donnell | NAHL | 88.6% | 87.2% | Aurora | D3 | 91.0% | 2.97 |
| Dane Couture | NAHL | 88.1% | 86.3% | Concordia | D3 | 87.3% | 2.94 |
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.