icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Green Bay Gamblers | USHL | 42 | 21 | 18 | 89.3% | 3.20 | 2 | 0.9983 | 82.4% |
| 2023-24 | Green Bay Gamblers | USHL | 22 | 11 | 6 | 90.0% | 3.14 | 1 | 0.9983 | 86.4% |
| 2022-23 | — | NAHL | 30 | 21 | 7 | 93.8% | 2.00 | 5 | 0.9843 | 95.2% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Western Michigan | D1 | 1 | 0 | 0 | — | — | 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 |
|---|---|---|---|---|---|---|
| Ryan Keyes | NCDC | 92.6% | 83.2% | Merrimack | 92.0% | 2.22 |
| Lucas Massie | USHL | 87.9% | 81.1% | Union | 80.5% | 5.73 |
| Alexander Tracy | USHL | 89.6% | 83.0% | Minnesota | 87.9% | 2.24 |
| Bruno Bruveris | USHL | 89.7% | 82.4% | Miami | 86.6% | 4.15 |
| Ryan Manzella | USHL | 90.4% | 83.1% | Michigan Tech | 89.5% | 3.17 |
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 |
| Nolan Hildebrand | BCHL | 89.3% | 81.9% | Babson | D3 | 87.8% | 3.82 |
| Dolan Gilbert | NA3HL | 91.0% | 81.2% | Concordia | D3 | 81.0% | 9.00 |
| Cameron Hrdlicka | SJHL | 89.6% | 83.0% | Concordia | D3 | 89.0% | 3.97 |
| 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.