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 | 41 | 19 | 16 | 91.3% | 2.65 | 4 | 0.9983 | 84.1% |
| 2021-22 | — | Allsvenskan | 1 | 0 | 0 | 100.0% | — | 0 | 1.0100 | 97.0% |
| 2021-22 | — | SHL | — | — | — | — | — | — | 1.0100 | — |
| 2021-22 | — | SuperElit | 34 | 20 | 13 | 90.0% | 3.05 | 3 | 0.9600 | 82.5% |
| 2021-22 | — | SHL-J20 | 34 | 20 | 13 | 90.0% | 3.05 | 3 | 0.9600 | 82.5% |
| 2020-21 | — | SHL | — | — | — | — | — | — | 1.0100 | — |
| 2020-21 | — | SuperElit | 4 | 3 | 1 | 90.0% | 2.98 | 0 | 0.9600 | 86.4% |
| 2020-21 | — | SHL-J20 | 4 | 3 | 1 | 90.0% | 2.98 | 0 | 0.9600 | 86.4% |
| 2019-20 | — | SuperElit | 1 | 0 | 1 | 80.0% | 6.00 | 0 | 0.9600 | 76.8% |
| 2019-20 | — | SHL-J20 | 1 | 0 | 1 | 80.0% | 6.00 | 0 | 0.9600 | 76.8% |
| 2018-19 | — | SuperElit | — | — | — | — | — | — | 0.9600 | — |
| 2018-19 | — | SHL-J20 | — | — | — | — | — | — | 0.9600 | — |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Merrimack | D1 | 39 | 21 | 16 | 92.0% | 2.55 | 1 |
| 2024-25 | Merrimack | D1 | 24 | 8 | 13 | 90.9% | 2.90 | 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 |
|---|---|---|---|---|---|---|
| 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 |
| Gavin Moffatt | USHL | 89.3% | 82.4% | 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 |
|---|---|---|---|---|---|---|---|
| Dean Hahn | USPHL-Premier | 91.6% | 84.1% | Salem State | D3 | 88.9% | 3.95 |
| Logan Palmer | USPHL-Premier | 92.1% | 84.5% | Western New England | D3 | 90.9% | 3.11 |
| Cameron Hrdlicka | SJHL | 89.6% | 83.0% | Concordia | D3 | 89.0% | 3.97 |
| Avery Rovira | EHL | 90.1% | 86.0% | Elmira | D3 | 88.9% | 3.91 |
| 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.