icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | USHL | 32 | 10 | 19 | 88.6% | 4.27 | 0 | 0.9980 | 76.6% |
| 2021-22 | — | NAHL | 35 | 21 | 6 | 92.2% | 2.27 | 1 | 0.9843 | 90.5% |
| 2020-21 | — | SJHL | 4 | 1 | 2 | 91.1% | 4.26 | 0 | 0.9700 | 88.4% |
| 2019-20 | — | NAHL | 1 | 0 | 1 | 85.7% | 5.00 | 0 | 0.9843 | 84.4% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Bemidji State | D1 | 12 | 5 | 5 | 89.2% | 2.65 | 1 |
| 2024-25 | Bemidji State | D1 | 3 | 1 | 1 | 88.6% | 2.30 | 0 |
| 2023-24 | Bemidji State | D1 | 3 | 0 | 0 | 80.0% | 5.38 | 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 |
|---|---|---|---|---|---|---|
| Aaron Randazzo | USHL | 88.8% | 77.0% | Air Force | 82.4% | 5.23 |
| Chad Veltri | USHL | 90.2% | 78.3% | Niagara | 93.1% | 2.10 |
| Yan Shostak | USHL | 91.1% | 78.6% | St. Cloud State | 89.7% | 3.08 |
| Alexander Tracy | USHL | 89.6% | 77.2% | Minnesota | 87.9% | 2.24 |
| Gavin Moffatt | USHL | 89.3% | 76.3% | Western Michigan | — | — |
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% | 79.8% | Framingham State | D3 | 83.3% | 8.53 |
| Gabe Rosek | NOJHL | 91.3% | 79.3% | Concordia | D3 | 90.2% | 4.56 |
| Will Pinney | NA3HL | 90.3% | 78.8% | Gustavus Adolphus | D3 | 85.8% | 4.05 |
| Nolan Hildebrand | AJHL | 87.4% | 77.5% | Babson | D3 | 87.8% | 3.82 |
| Dolan Gilbert | NA3HL | 91.0% | 78.2% | Concordia | D3 | 81.0% | 9.00 |
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.