icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | USHL | 44 | 27 | 10 | 89.6% | 2.50 | 3 | 0.9983 | 83.0% |
| 2020-21 | — | USHL | 18 | 9 | 7 | 88.9% | 2.66 | 1 | 0.9983 | 88.8% |
| 2019-20 | — | NAHL | 24 | 17 | 4 | 93.5% | 2.12 | 4 | 0.9843 | 92.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Minnesota | D1 | 39 | 21 | 11 | 92.7% | 1.80 | 5 |
| 2024-25 | Minnesota | D1 | 38 | 26 | 9 | 94.6% | 1.42 | 5 |
| 2023-24 | Minnesota | D1 | 28 | 13 | 10 | 91.0% | 2.50 | 2 |
| 2022-23 | Minnesota | D1 | 10 | 6 | 3 | 87.9% | 2.24 | 1 |
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 |
|---|---|---|---|---|---|---|
| Ryan Keyes | NCDC | 92.6% | 83.2% | Merrimack | 92.0% | 2.22 |
| Gavin Moffatt | USHL | 89.3% | 82.4% | Western Michigan | — | — |
| Aaron Randazzo | USHL | 88.8% | 82.5% | Air Force | 82.4% | 5.23 |
| Joshua Seeley | NAHL | 90.0% | 84.9% | Bentley | 82.6% | 8.58 |
| Chad Veltri | USHL | 90.2% | 83.9% | Niagara | 93.1% | 2.10 |
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 Hildebrand | AJHL | 87.4% | 82.5% | Babson | D3 | 87.8% | 3.82 |
| Josh Koziol | NA3HL | 93.3% | 83.8% | Augsburg | D3 | 71.4% | 5.76 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 83.7% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Owen Swanbon | USPHL-Premier | 90.4% | 83.4% | Framingham State | D3 | 83.3% | 8.53 |
| Dean Hahn | USPHL-Premier | 91.6% | 84.1% | Salem State | D3 | 88.9% | 3.95 |
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.