icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Dubuque Fighting Saints | USHL | 39 | 24 | 15 | 90.7% | 2.82 | 2 | 0.9983 | 84.1% |
| 2023-24 | Portland Winterhawks | WHL | 35 | 25 | 6 | 91.3% | 2.12 | 2 | 1.0047 | 88.5% |
| 2022-23 | — | WHL | 31 | 17 | 7 | 90.8% | 2.61 | 0 | 1.0047 | 91.3% |
| 2021-22 | — | USHL-Style-Czech | 31 | 22 | 8 | 91.1% | 2.57 | 3 | 0.9600 | 90.1% |
| 2020-21 | — | USHL-Style-Czech | 2 | 1 | 1 | 90.1% | 3.41 | 0 | 0.9600 | 86.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | North Dakota | D1 | 27 | 20 | 5 | 91.9% | 1.91 | 6 |
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 |
|---|---|---|---|---|---|---|
| Yan Shostak | USHL | 91.1% | 84.5% | St. Cloud State | 89.7% | 3.08 |
| Chad Veltri | USHL | 90.2% | 83.9% | Niagara | 93.1% | 2.10 |
| Aaron Randazzo | USHL | 88.8% | 82.5% | Air Force | 82.4% | 5.23 |
| Ben Bonisteel | OJHL | 92.6% | 84.6% | Canisius | 89.3% | 3.10 |
| Jack Williams | USHL | 90.8% | 84.5% | Notre Dame | 88.9% | 2.90 |
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 |
|---|---|---|---|---|---|---|---|
| Owen Swanbon | USPHL-Premier | 90.4% | 83.4% | Framingham State | D3 | 83.3% | 8.53 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 83.7% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Josh Koziol | NA3HL | 93.3% | 83.8% | Augsburg | D3 | 71.4% | 5.76 |
| Diego D'Alessandro | CCHL | 89.2% | 84.9% | King's | D3 | 86.5% | 4.68 |
| Michael Cammasso | USPHL-Premier | 92.4% | 85.1% | Johnson & Wales | D3 | 82.2% | 8.99 |
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.