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 | 30 | 15 | 14 | 89.7% | 2.88 | 0 | 0.9843 | 84.4% |
| 2021-22 | — | NAHL | 41 | 15 | 18 | 91.7% | 3.35 | 0 | 0.9843 | 89.5% |
| 2020-21 | — | NAHL | 15 | 4 | 3 | 92.2% | 2.43 | 0 | 0.9843 | 90.8% |
| 2019-20 | — | NAHL | 1 | 0 | 0 | 95.2% | 1.70 | 0 | 0.9843 | 93.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Norbert | D3 | 28 | — | — | 91.8% | 2.00 | 0 |
| 2024-25 | St. Norbert | D3 | 28 | — | — | 91.1% | 2.17 | 0 |
| 2023-24 | St. Norbert | D3 | 23 | 0 | 1 | 92.2% | 1.90 | 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 |
|---|---|---|---|---|---|---|
| Charles-Edward Gravel | QMJHL | 91.4% | 84.0% | Mercyhurst | 90.7% | 3.22 |
| Cole Plowman | MJHL | 93.4% | 85.4% | Alaska Fairbanks | 100.0% | — |
| Ryan Manzella | USHL | 90.4% | 83.1% | Michigan Tech | 89.5% | 3.17 |
| Ryan Keyes | NCDC | 92.6% | 83.2% | Merrimack | 92.0% | 2.22 |
| Joshua Seeley | NAHL | 90.0% | 84.9% | Bentley | 82.6% | 8.58 |
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 |
|---|---|---|---|---|---|---|---|
| Logan Palmer | USPHL-Premier | 92.1% | 84.5% | Western New England | D3 | 90.9% | 3.11 |
| Dean Hahn | USPHL-Premier | 91.6% | 84.1% | Salem State | D3 | 88.9% | 3.95 |
| Avery Rovira | EHL | 90.1% | 86.0% | Elmira | D3 | 88.9% | 3.91 |
| Cameron Hrdlicka | SJHL | 89.6% | 83.0% | Concordia | D3 | 89.0% | 3.97 |
| Logan Gorbitz | USPHL-Premier | 91.8% | 83.9% | Neumann | D3 | 84.4% | 5.24 |
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.